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66 KiB
Kontextual Engine Functional Requirements Specification V0.2
kontextual-engine
Prepared: 2026-05-05
Document type: Functional requirements specification
Status: Scope refinement draft
Aligned with: ProductRequirementsDocument.V0.2.md and INTENT.refined.md
1. System Overview
1.1 Product Summary
kontextual-engine is a headless knowledge operations engine for making heterogeneous information assets persistent, contextual, governed, retrievable, transformable, and agent-operable.
The system provides reusable backend capabilities for applications, workflows, services, and AI agents that need to operate documents, files, records, notes, datasets, generated outputs, and content collections as durable knowledge assets.
This Functional Requirements Specification defines the externally observable functional behavior of the system. It does not prescribe a specific storage backend, search engine, AI provider, user interface, deployment model, or source-system implementation.
1.2 Functional Scope
The FRS covers the following functional areas:
- knowledge asset registry and persistent identity
- ingestion from heterogeneous formats and sources
- normalization and extraction into common representations
- metadata, classification, context modeling, and relationships
- search, filtering, querying, and permission-aware retrieval
- transformation, composition, and traceable derived artifacts
- workflow and job orchestration
- permissions, policy enforcement, governance, audit, and lifecycle behavior
- versioning, provenance, and dependency traceability
- agent-safe AI interaction through explicit operations
- API-first access, integration, and extensibility
- observability, administration, export, portability, and error handling
The system is not specified as a finished ECM, DMS, CMS, intranet, visual editor, file-sync client, pure vector database, or single-purpose AI chat application. Those may be built on top of the engine or integrated with it.
1.3 Functional Operating Model
The expected functional flow is:
knowledge sources
-> ingestion and normalization
-> stable knowledge asset identity
-> metadata, context, relationships, provenance, permissions, and lifecycle state
-> governed retrieval, transformation, workflow, and agent-safe operation
-> APIs, automation interfaces, exports, and downstream applications
The engine owns the middle layer: durable identity, context, governance, retrieval, transformation, workflow state, traceability, and operational interfaces.
1.4 Requirement Priority Model
Functional requirements use the following priority levels:
- P0 — Core engine requirement: required for a credible MVP of the knowledge operations engine.
- P1 — Enterprise readiness requirement: required for strong corporate adoption, governance, scale, and operational maturity.
- P2 — Expansion requirement: useful for mature deployments, vertical packages, advanced workflows, or broader market coverage.
2. Actors and Interfaces
2.1 Primary Actors
| Actor | Description | Typical Functional Needs |
|---|---|---|
| Human knowledge worker | A person using applications built on the engine. | Search, inspect, validate, compose, review, and reuse knowledge assets. |
| Developer | A person building applications, integrations, workflows, extensions, or services on the engine. | Stable APIs, schemas, events, SDKs, predictable errors, and testable behavior. |
| Platform operator | A person managing engine operation. | Ingestion status, job control, re-indexing, observability, audit access, and recovery tools. |
| Business process owner | A person responsible for a knowledge workflow, governance rule, or lifecycle process. | Workflow definition, approval rules, policy checks, exceptions, and reporting. |
| Reviewer or approver | A human participant in validation, correction, approval, or publication workflows. | Review queues, source context, decisions, comments, and audit trail. |
| External application | A product or service that uses the engine through APIs. | Asset operations, search, retrieval, workflow invocation, and export. |
| Automation system | Deterministic automation invoking recurring jobs or workflows. | Scheduled ingestion, enrichment, validation, transformation, synchronization, and archival. |
| AI agent | An AI system acting through explicit tool-like operations. | Bounded context access, source-grounded retrieval, transformations, workflow actions, and review submission. |
| Source system | A file store, repository, database, content system, document platform, or business application supplying assets. | Connector-mediated ingestion, permission context, metadata, source references, and update events. |
| Downstream system | A target application, storage location, publication channel, archive, or workflow system receiving outputs. | Exported assets, derived artifacts, events, and lineage-preserving integration. |
2.2 System Interfaces
| Interface | Required Role |
|---|---|
| Service API | Primary interface for asset, metadata, retrieval, transformation, workflow, permission, audit, export, and agent operations. |
| Programmatic API or SDK | Developer-facing abstraction over the service API where provided. |
| Connector and adapter interface | Source-system and downstream-system integration boundary. |
| Workflow and job interface | Submission, execution, tracking, retry, cancellation, and result inspection for jobs and workflows. |
| Agent operation interface | Explicit bounded operations for AI agents with permission checks, audit logging, and review gates. |
| Admin and observability interface | Operational inspection, error recovery, audit access, metrics, and governance reporting. |
| Export and portability interface | Governed extraction of assets, metadata, relationships, versions, provenance, audit references, and derived artifacts. |
2.3 Authorization Context
Every material operation should be evaluated against an authorization context containing, where available:
- actor identity
- delegated user or service context
- role and group membership
- asset-specific policy
- source-system policy or effective permission data
- sensitivity classification
- lifecycle state
- workflow state
- operation type and requested output
AI agents must not receive implicit privileged access. They are actors with explicit scope, permissions, task boundaries, and audit requirements.
3. Functional Entities
| Entity | Functional Meaning |
|---|---|
| Knowledge asset | A durable unit of knowledge managed by the engine, such as a file, document, record, dataset, note, generated output, or content item. |
| Asset ID | Stable identifier assigned by the engine and used independent of path, filename, source URL, storage backend, or representation. |
| Source reference | Information that identifies where an asset originated, including source system, path, URL, external ID, checksum, or connector reference where available. |
| Source representation | The original or source-near form of the asset, preserved or referenced where configured. |
| Normalized representation | Engine-usable representation created from ingestion and extraction, suitable for search, metadata, transformation, workflows, and agent context. |
| Metadata | Structured descriptive information attached to an asset, including standard and custom fields. |
| Classification | A label or category used for type, topic, sensitivity, lifecycle, operational purpose, or governance. |
| Contextual entity | A non-asset entity such as person, project, case, customer, product, process, topic, source system, or business object. |
| Relationship | A typed link between assets or between an asset and a contextual entity. |
| Version | A traceable state of asset content, metadata, relationships, lifecycle, or derived artifact. |
| Derived artifact | An output produced from one or more source assets through transformation, composition, extraction, summarization, generation, or workflow. |
| Transformation run | A recorded operation that creates, updates, or derives information from assets. |
| Workflow run | An executed instance of a workflow template or job definition. |
| Policy | A rule or rule set controlling permissions, lifecycle, retention, review, transformation, publication, export, or agent behavior. |
| Audit event | A record of a material operation, actor, target, time, outcome, and relevant policy context. |
| Export package | A governed package containing selected assets and supporting metadata, relationships, versions, provenance, audit references, and manifests. |
4. Functional Requirements
Each requirement below specifies externally observable system behavior. Verification should be possible through API contract tests, integration tests, workflow tests, permission tests, audit-log inspection, export validation, or operator-facing status inspection.
4.1 Knowledge Asset Registry and Persistence
| ID | Priority | Requirement | Functional Behavior | Acceptance Signal |
|---|---|---|---|---|
| FR-001 | P0 | Create knowledge assets | The system shall create a knowledge asset from submitted content, structured data, or a source reference. | A caller can submit content or a source reference and receive a persisted asset record with an asset ID and initial state. |
| FR-002 | P0 | Assign stable asset identity | The system shall assign an asset ID that remains stable across rename, move, re-ingestion, representation change, and transformation. | An asset can change path, filename, source representation, or normalized representation without losing its asset ID or history. |
| FR-003 | P0 | Persist asset state | The system shall persist asset content references, normalized content, metadata, relationships, lifecycle state, permissions, provenance, and operational status where available. | A persisted asset can be retrieved with its current content reference, normalized representation, metadata, relationships, lifecycle state, and provenance. |
| FR-004 | P0 | Retrieve assets by identifier | The system shall retrieve a knowledge asset by stable asset ID. | A valid asset ID returns the matching asset or an explicit permission or not-found error. |
| FR-005 | P0 | Update asset content and metadata | The system shall update asset content, normalized representation, metadata, relationships, and lifecycle state through explicit operations. | Updates are persisted, audit logged, and visible through subsequent retrieval calls. |
| FR-006 | P0 | Retire or delete assets under policy | The system shall support asset retirement, soft deletion, and deletion requests subject to lifecycle, retention, legal hold, and permission checks. | A deletion request either changes the asset to the expected terminal state or returns a structured policy error. |
| FR-007 | P0 | Group assets into collections | The system shall group assets into collections, domains, projects, spaces, or equivalent organizational containers. | Assets can be assigned to and retrieved from one or more configured containers. |
| FR-008 | P0 | Represent original and normalized forms | The system shall distinguish between source/original representation and normalized representation used for retrieval and workflows. | A caller can inspect source reference data and normalized content without confusing the two representations. |
| FR-009 | P1 | Detect duplicate or repeated ingestion | The system should identify likely duplicate assets or repeated ingestion events using configured identity, source, checksum, or fingerprint rules. | Repeated ingestion of the same source can update the existing asset or produce a duplicate warning according to configured policy. |
| FR-010 | P1 | Support aliases and supersession | The system should support aliases, redirects, canonical asset references, and supersession relationships. | A renamed, replaced, or superseded asset remains discoverable through configured aliases or successor references. |
4.2 Ingestion and Normalization
| ID | Priority | Requirement | Functional Behavior | Acceptance Signal |
|---|---|---|---|---|
| FR-020 | P0 | Submit ingestion jobs | The system shall create ingestion jobs from direct uploads, local or remote source references, connector events, or API requests. | A caller can submit an ingestion request and receive a job ID with observable status. |
| FR-021 | P0 | Ingest baseline heterogeneous formats | The system shall support ingestion of text, markdown, common office documents, PDFs, and structured datasets in the baseline implementation. | Each baseline format can be ingested into a knowledge asset with normalized content and source provenance. |
| FR-022 | P0 | Record ingestion provenance | The system shall record source system, source location, source identifier, ingestion time, extractor, transformation path, and actor where available. | Each ingested asset can report where it came from, when it was ingested, and how it was extracted. |
| FR-023 | P0 | Normalize content | The system shall convert ingested content into a common internal representation suitable for search, metadata, relationships, transformations, and workflows. | Assets from different supported formats can be queried and transformed through common APIs. |
| FR-024 | P0 | Extract structural elements | The system shall extract structural elements such as title, sections, headings, paragraphs, tables, links, and embedded references where supported by the source format. | The normalized representation exposes structure when the extractor can recover it. |
| FR-025 | P0 | Expose ingestion status and failures | The system shall expose queued, running, completed, failed, retried, and partially completed ingestion states. | Operators and callers can inspect failure reason, affected assets, correlation ID, and retry options. |
| FR-026 | P1 | Support incremental re-ingestion | The system should re-ingest changed sources without corrupting identity, version history, provenance, permissions, or relationships. | A changed source can be synchronized while preserving the stable asset ID and creating a traceable update. |
| FR-027 | P1 | Support pluggable extractors and connectors | The system should allow new source connectors and format extractors to be added without changing core engine behavior. | A new connector or extractor can register capabilities, submit assets, and return normalized content through a defined contract. |
| FR-028 | P1 | Validate ingestion output | The system should validate normalized content, required metadata, provenance, and policy constraints before marking ingestion complete. | Invalid ingestion output produces structured validation errors and does not silently enter the trusted asset set. |
| FR-029 | P2 | Support advanced OCR and layout extraction | The system may support OCR, visual layout extraction, table reconstruction, and image-region extraction for scanned or complex documents. | A scanned or layout-heavy document can produce text, structure, and confidence signals where configured. |
| FR-030 | P2 | Support media-derived representations | The system may create transcripts, captions, thumbnails, previews, embeddings, or metadata for image, audio, and video assets. | Rich-media assets can expose derived representations suitable for retrieval and governance. |
4.3 Metadata, Classification, and Context Modeling
| ID | Priority | Requirement | Functional Behavior | Acceptance Signal |
|---|---|---|---|---|
| FR-040 | P0 | Manage explicit metadata | The system shall create, read, update, and remove explicit metadata fields on knowledge assets. | A caller can set and retrieve asset metadata through the API with audit logging. |
| FR-041 | P0 | Support standard metadata fields | The system shall support standard metadata fields for asset type, owner, source, domain, project or context, sensitivity, lifecycle state, tags, timestamps, and custom labels. | Standard metadata can be used consistently for filtering, permissions, workflows, and audit. |
| FR-042 | P0 | Support custom metadata schemas | The system shall allow configured schemas for domain-specific metadata without hard-coding one domain model into the engine. | A configured schema can validate and expose custom fields for a collection or asset type. |
| FR-043 | P0 | Assign classifications | The system shall assign classifications such as document type, topic, sensitivity, lifecycle status, and operational category manually or through configured automation. | Classifications can be stored, queried, corrected, and audited. |
| FR-044 | P0 | Define relationships between assets | The system shall create, retrieve, update, and remove typed relationships between knowledge assets. | Assets can be linked as source, derivative, reference, duplicate, successor, dependency, version, citation, or related item according to configured relationship types. |
| FR-045 | P0 | Represent contextual entities | The system shall represent contextual entities such as people, teams, projects, cases, customers, products, processes, source systems, topics, and generated artifacts. | Assets can be linked to contextual entities and retrieved through those links. |
| FR-046 | P0 | Query context | The system shall allow querying assets by relationship, contextual entity, collection, source, metadata, and lifecycle state. | A caller can retrieve all assets connected to a project, case, topic, person, process, or other configured entity. |
| FR-047 | P1 | Maintain relationship semantics | The system should support relationship direction, type, validity interval, confidence, actor, and provenance. | A relationship can indicate who or what created it, why it exists, and whether it is current, inferred, or manually confirmed. |
| FR-048 | P1 | Support inferred metadata review | The system should distinguish inferred metadata or relationships from human-confirmed metadata or relationships. | AI- or automation-generated annotations can be reviewed, accepted, corrected, or rejected. |
| FR-049 | P1 | Validate metadata against schemas | The system should enforce required fields, data types, allowed values, and conditional rules according to configured schemas. | Invalid metadata updates return structured validation errors. |
| FR-050 | P2 | Support domain-specific context packages | The system may allow deployable domain packages for legal, support, research, compliance, engineering, or marketing semantics. | A domain package can add schema, relationship types, workflow templates, and validation rules without redefining the core engine. |
4.4 Search, Query, and Retrieval
| ID | Priority | Requirement | Functional Behavior | Acceptance Signal |
|---|---|---|---|---|
| FR-060 | P0 | Retrieve by asset ID | The system shall retrieve assets by stable asset ID through an API operation. | A permitted caller receives the current asset record, selected representations, metadata, relationships, and provenance. |
| FR-061 | P0 | Search by text | The system shall support text search across normalized content for supported ingested assets. | A query returns matching assets with relevance ordering and result metadata. |
| FR-062 | P0 | Filter by metadata and lifecycle state | The system shall support filtering by asset type, collection, source, owner, tags, classification, sensitivity, lifecycle state, and timestamps. | A query can combine text search with metadata and lifecycle filters. |
| FR-063 | P0 | Retrieve by relationship and context | The system shall support retrieval by relationships and contextual entities. | A caller can retrieve assets related to a given project, case, topic, source asset, generated artifact, or workflow run. |
| FR-064 | P0 | Return source-grounded result data | The system shall return asset IDs, titles, snippets or matched regions, relevant metadata, source references, and relationship context where available. | Search results provide enough information to inspect why a result was returned and where it originated. |
| FR-065 | P0 | Enforce permission-aware retrieval | The system shall apply permission and policy checks before returning asset content, metadata, snippets, derived artifacts, or relationship data. | Unauthorized assets do not appear in results, snippets, generated answers, exports, or relationship traversals. |
| FR-066 | P0 | Support stable pagination and sorting | The system shall support deterministic pagination and sorting for query results. | Repeated equivalent queries return stable pages within documented consistency limits. |
| FR-067 | P1 | Support facets and aggregations | The system should return facets or aggregations for configured metadata and classifications. | A caller can display counts by source, type, owner, sensitivity, lifecycle state, or configured taxonomy. |
| FR-068 | P1 | Support semantic retrieval | The system should support semantic or vector-based retrieval in addition to lexical search where configured. | A semantic query can return relevant assets even when exact terms differ, while preserving permissions and provenance. |
| FR-069 | P1 | Support grounded answer retrieval | The system should provide retrieval packages suitable for grounded answers, summaries, and analysis. | A grounded answer workflow receives supporting passages, citations, source IDs, metadata, and permission context. |
| FR-070 | P1 | Capture retrieval feedback | The system should allow users, applications, or evaluation jobs to record useful, irrelevant, missing, or unsafe retrieval feedback. | Feedback is stored with query context and can be used for quality analysis. |
| FR-071 | P2 | Support federated query patterns | The system may support querying across external repositories without fully ingesting all content when connector policy allows. | A query can combine engine-managed assets with connector-mediated external results while preserving source permissions. |
4.5 Transformation, Composition, and Derived Artifacts
| ID | Priority | Requirement | Functional Behavior | Acceptance Signal |
|---|---|---|---|---|
| FR-080 | P0 | Execute transformations | The system shall execute configured transformations over one or more knowledge assets. | A caller can request a transformation and receive a run ID, status, and result or structured error. |
| FR-081 | P0 | Compose outputs from multiple assets | The system shall compose derived outputs from multiple source assets where configured. | A report, summary, extract, view, bundle, or structured representation can be created from selected source assets. |
| FR-082 | P0 | Persist derived artifacts | The system shall persist derived outputs as knowledge assets or artifact records with stable identity. | A derived artifact can be retrieved, queried, governed, versioned, and related to its sources. |
| FR-083 | P0 | Record transformation lineage | The system shall record source assets, source versions where available, operation type, parameters, actor, time, policy context, and output artifact for each transformation. | A derived artifact can explain which sources and operation produced it. |
| FR-084 | P0 | Support parameterized transformations | The system shall support transformation parameters such as output type, scope, template, model, extraction fields, target schema, and review policy where applicable. | Transformation results include the parameters necessary to interpret or reproduce the operation within documented limits. |
| FR-085 | P0 | Enforce transformation permissions | The system shall enforce access and policy checks before reading source assets, generating outputs, or storing derived artifacts. | A caller cannot use transformation workflows to bypass retrieval, export, sensitivity, or lifecycle policies. |
| FR-086 | P1 | Support human review for transformations | The system should support review, approval, correction, and rejection of derived artifacts before publication or downstream use. | A transformation can produce a draft artifact that requires human decision before being marked approved. |
| FR-087 | P1 | Support controlled re-runs | The system should allow transformations to be re-run against the same or newer source versions with explicit lineage. | A re-run produces a new traceable run record and does not overwrite prior results without policy permission. |
| FR-088 | P1 | Compare derived artifacts | The system should compare derived artifacts across source versions, transformation parameters, or review states. | A caller can inspect differences between two summaries, reports, extracts, or generated representations. |
| FR-089 | P2 | Publish transformation outputs | The system may publish approved derived artifacts to downstream systems through configured adapters. | A derived artifact can be delivered to an external application while retaining lineage and publication audit. |
| FR-090 | P2 | Support reusable transformation templates | The system may support configurable templates for recurring summaries, reports, extracts, and generated artifacts. | A template can be versioned, invoked, audited, and reused across workflows. |
4.6 Workflow and Job Orchestration
| ID | Priority | Requirement | Functional Behavior | Acceptance Signal |
|---|---|---|---|---|
| FR-100 | P0 | Define workflow templates | The system shall define reusable workflow or job templates containing steps, dependencies, inputs, outputs, policies, and failure behavior. | A workflow template can be created and invoked through the API. |
| FR-101 | P0 | Execute workflows | The system shall execute multi-step workflows over assets, collections, queries, source events, or submitted inputs. | A workflow run can ingest, enrich, validate, transform, review, publish, synchronize, archive, or export knowledge according to the template. |
| FR-102 | P0 | Track workflow state | The system shall expose workflow run state, step state, actor, timestamps, input references, output references, and error status. | A caller can inspect queued, running, waiting, completed, failed, canceled, and retried states. |
| FR-103 | P0 | Respect step dependencies | The system shall execute workflow steps according to declared dependencies and preconditions. | A dependent step does not run until required prior steps succeed or enter an allowed alternate state. |
| FR-104 | P0 | Return workflow results | The system shall return workflow outputs, generated artifacts, updated assets, validation results, and failure details. | A completed workflow has observable outputs or an explicit no-output result. |
| FR-105 | P0 | Retry, resume, and cancel jobs | The system shall support retry, resume, and cancellation behavior for workflows and jobs where operation semantics allow. | A failed job can be retried from a safe state, resumed, or canceled with audit and visible outcome. |
| FR-106 | P0 | Audit workflow operations | The system shall audit workflow template changes, run starts, step executions, retries, cancellations, approvals, failures, and outputs. | A workflow run can be reconstructed from audit and run records. |
| FR-107 | P1 | Support event and schedule triggers | The system should trigger workflows from source changes, API events, schedules, lifecycle transitions, review decisions, and external webhooks. | A configured trigger starts the intended workflow and records trigger context. |
| FR-108 | P1 | Support human tasks | The system should support human review, validation, approval, correction, rejection, and exception-handling tasks inside workflows. | A workflow can pause for an assigned human decision and continue according to the result. |
| FR-109 | P1 | Maintain exception queues | The system should expose failed, blocked, low-confidence, policy-conflicted, or review-required workflow items as actionable queues. | Operators can list, inspect, assign, retry, approve, reject, or escalate exception items. |
| FR-110 | P2 | Support cross-system orchestration | The system may orchestrate workflows involving external ECM, CMS, DMS, ERP, CRM, ITSM, HR, support, storage, or publishing systems. | A workflow can call external systems through adapters while retaining engine-side state and audit. |
4.7 Permissions, Governance, Audit, and Lifecycle
| ID | Priority | Requirement | Functional Behavior | Acceptance Signal |
|---|---|---|---|---|
| FR-120 | P0 | Represent actors | The system shall represent human users, applications, automation systems, service accounts, and AI agents as actors with explicit identity context. | Every material operation can be associated with an actor or service principal. |
| FR-121 | P0 | Authorize operations | The system shall authorize retrieval, mutation, transformation, workflow, export, and agent operations based on actor, role, group, asset policy, sensitivity, lifecycle state, and source policy where available. | Unauthorized operations fail with structured authorization errors and do not leak protected content. |
| FR-122 | P0 | Enforce sensitivity and lifecycle constraints | The system shall apply sensitivity, lifecycle, review, publication, retention, deletion, and archival constraints to relevant operations. | A restricted asset cannot be transformed, exported, published, or deleted unless policy allows. |
| FR-123 | P0 | Preserve source permissions where available | The system shall store and apply source-system permission references or effective access rules when supplied by connectors. | Retrieval and derived operations respect source permissions or fail closed when required permission context is unavailable. |
| FR-124 | P0 | Audit material operations | The system shall audit asset creation, ingestion, update, deletion, metadata change, relationship change, permission change, query, transformation, workflow action, export, and agent operation according to configured audit policy. | Audit events include actor, operation, asset or job reference, timestamp, outcome, correlation ID, and policy context where available. |
| FR-125 | P0 | Query audit history | The system shall allow authorized callers to query audit events by asset, actor, operation, workflow, time range, source, and outcome. | An auditor can reconstruct who or what acted on an asset and when. |
| FR-126 | P0 | Fail closed on ambiguous access | The system shall deny or withhold protected content when permission or policy state is missing, stale, or ambiguous according to configured safety rules. | Ambiguous policy state produces an explicit error, hold, or redacted result rather than silent exposure. |
| FR-127 | P1 | Manage retention policies | The system should apply configured retention policies to assets, metadata, versions, audit events, and derived artifacts. | Assets subject to retention cannot be deleted before allowed disposition unless policy permits. |
| FR-128 | P1 | Support legal hold | The system should place assets, versions, metadata, derived artifacts, and relevant audit history under legal or compliance hold. | A held item cannot be altered or deleted in violation of the hold policy. |
| FR-129 | P1 | Support archival and defensible deletion | The system should support archival, disposal review, deletion approval, and deletion evidence for governed assets. | A deletion action produces traceable evidence or is blocked by retention, hold, or permission policy. |
| FR-130 | P1 | Synchronize permission changes | The system should update effective access when source-system permissions, internal roles, group membership, or policy rules change. | Permission changes propagate to retrieval, transformation, export, and agent access within documented latency. |
| FR-131 | P1 | Produce governance reports | The system should generate reports for retention coverage, policy exceptions, legal holds, access anomalies, stale assets, and audit completeness. | An authorized operator can export governance status for selected scopes. |
| FR-132 | P2 | Integrate with external policy and DLP systems | The system may integrate with external identity, classification, data loss prevention, records, privacy, or compliance systems. | External policy signals can influence access, transformation, export, and lifecycle decisions. |
4.8 Versioning and Provenance
| ID | Priority | Requirement | Functional Behavior | Acceptance Signal |
|---|---|---|---|---|
| FR-140 | P1 | Version asset content | The system should track versions of asset content or source references when assets change. | A caller can list versions and retrieve a selected version where policy permits. |
| FR-141 | P1 | Version metadata and relationships | The system should track changes to metadata, classification, lifecycle state, and relationships. | A caller can inspect how metadata or relationships changed over time. |
| FR-142 | P1 | Compare and restore versions | The system should compare versions and restore a prior version subject to permission and lifecycle policy. | A restore operation creates a new auditable change rather than erasing history. |
| FR-143 | P0 | Expose source provenance | The system shall expose source provenance for ingested assets, including source reference and ingestion path where available. | A user, application, workflow, or agent can determine the origin of an asset. |
| FR-144 | P0 | Expose derived-artifact lineage | The system shall expose lineage for generated or transformed artifacts. | A summary, extract, report, or generated representation can point back to source assets and transformation runs. |
| FR-145 | P1 | Support dependency impact analysis | The system should identify derived artifacts, workflows, indexes, or downstream integrations that depend on a changed source asset. | A source update can show which artifacts or workflows may need refresh or review. |
| FR-146 | P2 | Support provenance graph traversal | The system may support graph-style traversal across sources, versions, transformations, workflows, reviews, and outputs. | A caller can query multi-hop lineage and dependency paths. |
4.9 Agent-Safe AI Interaction
| ID | Priority | Requirement | Functional Behavior | Acceptance Signal |
|---|---|---|---|---|
| FR-160 | P0 | Register AI agents as explicit actors | The system shall treat AI agents as explicit actors or delegated actors, not as implicit privileged internal processes. | Agent operations include agent identity, delegated user or service context where applicable, and policy scope. |
| FR-161 | P0 | Expose a bounded operation catalog | The system shall expose explicit agent-usable operations for inspection, retrieval, metadata enrichment, classification, transformation, workflow invocation, and review submission. | An agent can only act through documented operations with declared inputs, outputs, and permissions. |
| FR-162 | P0 | Apply permissions to agent operations | The system shall apply the same or stricter permission and policy checks to agent operations as to human, application, or automation operations. | An agent cannot retrieve, infer, transform, export, or publish content beyond its authorized scope. |
| FR-163 | P0 | Provide context packages | The system shall provide agents with bounded context packages containing selected assets, snippets, metadata, relationships, provenance, task instructions, and policy constraints. | Agent context is explicit, source-grounded, and does not require unrestricted repository access. |
| FR-164 | P0 | Audit agent operations | The system shall log agent reads, searches, transformations, metadata changes, workflow actions, generated artifacts, and review submissions. | An auditor can distinguish agent actions from human and deterministic automation actions. |
| FR-165 | P0 | Require review gates where policy demands | The system shall require human review or deny operations for destructive, sensitive, externally published, or high-impact agent actions when configured policy requires it. | A sensitive agent operation enters a review state or fails with a policy error rather than executing automatically. |
| FR-166 | P1 | Support grounded AI answer workflows | The system should support AI-assisted answers, summaries, and analyses that cite supporting assets and preserve source context. | Generated answers include source references and can be audited for supporting evidence. |
| FR-167 | P1 | Remain provider neutral | The system should support AI provider, embedding model, reranker, and prompt strategy substitution through configured adapters. | Changing an AI provider does not require redefining core asset, permission, provenance, or workflow models. |
| FR-168 | P1 | Constrain agent tasks | The system should support task scopes, budgets, time limits, allowed operation lists, and approval requirements for agent workflows. | Agent execution stops or requests review when boundaries are reached. |
| FR-169 | P2 | Support multi-step agent workflows | The system may support agent workflows that plan, execute, monitor, request review, recover from failures, and produce traceable artifacts. | A multi-step agent task can be replayed or inspected from operation logs and workflow state. |
4.10 API, Integration, and Extensibility
| ID | Priority | Requirement | Functional Behavior | Acceptance Signal |
|---|---|---|---|---|
| FR-180 | P0 | Provide service APIs | The system shall expose core capabilities through service APIs for assets, metadata, relationships, ingestion, retrieval, transformations, workflows, permissions, audit, and agent operations. | Core operations can be performed without requiring a specific user interface or CLI. |
| FR-181 | P0 | Provide stable programmatic contracts | The system shall define stable request, response, error, pagination, filtering, authentication, and authorization contracts for programmatic clients. | External clients can integrate through documented contracts and receive predictable responses. |
| FR-182 | P0 | Accept external processing results | The system shall accept results from external processors, such as extractors, classifiers, enrichment services, transformation services, or AI systems, through controlled interfaces. | External results can be attached to assets as metadata, relationships, normalized representations, or derived artifacts with provenance. |
| FR-183 | P1 | Support source adapters | The system should provide an adapter model for source repositories, file stores, document systems, databases, content platforms, and application systems. | A source adapter can submit assets, source references, permission context, and update events through defined interfaces. |
| FR-184 | P1 | Emit events and webhooks | The system should emit events for asset changes, ingestion completion, workflow status, policy exceptions, derived artifact creation, and review decisions. | External systems can subscribe to engine events and react without polling every operation. |
| FR-185 | P1 | Support extensible schemas and plugins | The system should allow custom metadata schemas, relationship types, workflow steps, transformations, validators, and policy checks to be added through extensions. | An extension can add domain behavior without modifying core engine code. |
| FR-186 | P1 | Abstract implementation backends | The system should abstract storage, index, queue, workflow, AI provider, and model backends where practical. | A deployment can swap supported backends without changing externally visible asset semantics. |
| FR-187 | P1 | Version APIs | The system should version APIs and avoid breaking existing integrations without documented migration paths. | A client pinned to a supported API version continues to operate within the version support policy. |
| FR-188 | P2 | Support extension registry patterns | The system may provide a registry for connectors, extractors, transformations, policy modules, and domain packages. | Operators can discover, enable, disable, and inspect extensions from a managed registry. |
4.11 Observability and Administration
| ID | Priority | Requirement | Functional Behavior | Acceptance Signal |
|---|---|---|---|---|
| FR-200 | P0 | Expose job and ingestion status | The system shall expose current and historical status for ingestion jobs, transformation runs, workflow runs, and exports. | Operators can inspect state, duration, input, output, actor, and failure details. |
| FR-201 | P0 | Return correlation identifiers | The system shall return correlation IDs or trace references for errors, jobs, workflows, and material operations. | A reported error can be linked to system logs and audit records. |
| FR-202 | P0 | Support administrative recovery actions | The system shall support authorized retry, re-run, re-index, cancel, quarantine, and repair actions where safe. | An operator can recover from common ingestion, workflow, indexing, and transformation failures without directly modifying storage. |
| FR-203 | P1 | Expose operational metrics | The system should expose metrics for ingestion throughput, query latency, API latency, workflow completion, job failure, queue age, reprocessing success, and storage/index health. | Operators can monitor service health and compare implementation quality against target KPIs. |
| FR-204 | P1 | Expose retrieval quality signals | The system should expose retrieval quality feedback, zero-result rate, low-confidence result rate, click or selection signals where available, and evaluation results. | Product teams can identify poor retrieval behavior and measure improvement over time. |
| FR-205 | P1 | Expose AI operation and cost signals | The system should expose model calls, token or compute usage where available, transformation cost, answer cost, agent task cost, and provider errors. | Operators can attribute AI usage and cost to workflows, assets, agents, or applications. |
| FR-206 | P1 | Support governance inspection | The system should allow authorized inspection of permission coverage, policy gaps, stale permissions, missing metadata, lifecycle exceptions, and audit completeness. | Governance operators can identify assets that are under-classified, overexposed, stale, or policy-conflicted. |
| FR-207 | P2 | Support policy simulation | The system may simulate the impact of permission, lifecycle, retention, and export policy changes before enforcement. | An operator can preview affected assets, workflows, exports, and agent scopes before activating a policy change. |
4.12 Export, Portability, and Migration
| ID | Priority | Requirement | Functional Behavior | Acceptance Signal |
|---|---|---|---|---|
| FR-220 | P1 | Export asset packages | The system should export assets, normalized representations, metadata, relationships, provenance, versions, audit references, and derived artifacts according to permission and policy. | An export package contains enough information to inspect or migrate selected knowledge assets. |
| FR-221 | P1 | Export by scope | The system should export by asset ID, collection, query, workflow run, source system, lifecycle state, date range, or governance policy. | An authorized caller can export a governed subset without manual database access. |
| FR-222 | P1 | Include manifests and integrity data | The system should include manifests, counts, checksums or hashes, schema versions, export time, actor, and policy context in export packages. | An exported package can be validated for completeness and integrity. |
| FR-223 | P1 | Support re-import or migration validation | The system should support validation of exported packages for re-import, migration, or downstream processing. | An export can be checked before migration and produce a validation report. |
| FR-224 | P2 | Support long-term archival formats | The system may support archival formats and preservation metadata for long-lived governed assets. | An archive package preserves source, context, lifecycle, and provenance information for long-term use. |
| FR-225 | P2 | Produce migration reports | The system may produce migration reports for completeness, skipped assets, unsupported fields, permission gaps, and relationship preservation. | A migration run can be evaluated before decommissioning a source system. |
4.13 Error Handling and Functional Correctness
| ID | Priority | Requirement | Functional Behavior | Acceptance Signal |
|---|---|---|---|---|
| FR-240 | P0 | Return structured errors | The system shall return structured errors for invalid input, unauthorized access, unsupported format, failed ingestion, policy conflict, validation failure, dependency failure, and internal failure. | Clients receive machine-readable error code, message, correlation ID, operation, and remediation hint where available. |
| FR-241 | P0 | Avoid silent failures | The system shall not silently ignore failures that affect persistence, identity, permissions, retrieval correctness, transformation outputs, workflow state, or auditability. | Material failures produce visible job status, error records, audit records, or caller errors. |
| FR-242 | P0 | Validate inputs | The system shall validate asset, metadata, query, transformation, workflow, permission, export, and agent-operation inputs before execution. | Invalid input fails before partial state change unless the operation explicitly supports partial completion. |
| FR-243 | P0 | Report partial failures | The system shall report partial failures in batch ingestion, transformation, workflow, query, and export operations. | A batch operation reports succeeded, failed, skipped, quarantined, and retriable items separately. |
| FR-244 | P1 | Support idempotency | The system should support idempotency keys or equivalent safeguards for create, ingest, transform, workflow, and export operations where duplicate execution would be harmful. | A repeated request with the same idempotency context does not create unintended duplicate assets or jobs. |
| FR-245 | P1 | Support conflict detection | The system should detect concurrent update conflicts for content, metadata, relationships, policies, and workflow state. | A conflicting update returns a structured conflict response with the current version or resolution guidance. |
5. Functional Constraints
The following constraints apply across all functional requirements:
- The system must be API-first and must not require a specific user interface or CLI for core operation.
- The system must remain format-agnostic and must not be constrained to one authoring or storage format.
- The system must remain provider-neutral with respect to AI model provider, embedding model, search engine, workflow engine, storage backend, and deployment platform where practical.
- The system must treat stable asset identity, source provenance, permissions, auditability, and transformation lineage as core functional concerns.
- The system must not use transformations, workflows, exports, search snippets, or AI-generated answers to bypass access controls.
- The system must distinguish source content, normalized representation, and derived artifacts.
- The system must support both human and machine actors, including applications, automation systems, and AI agents.
- The system must surface material failure states explicitly through structured errors, job status, audit events, or operator-visible diagnostics.
6. Core Capability KPIs
The following KPIs should be used to evaluate implementation quality and to compare the engine against relevant alternatives.
| Capability | Primary KPIs |
|---|---|
| Multi-source ingestion | Connector coverage; ingestion success rate; source-update-to-index latency |
| Format normalization and extraction | Extraction accuracy or F1; unsupported-format rate; processing cost per asset |
| Persistent asset identity | Duplicate-detection rate; identity collision rate; percentage of assets with stable IDs |
| Metadata and classification | Metadata completeness; classification accuracy; manual correction rate |
| Context modeling and relationships | Relationship coverage; graph/query completeness; average context depth per asset |
| Search and retrieval | Precision@k or NDCG; p95 query latency; zero-result rate |
| Grounded AI answers and RAG | Grounded-answer accuracy; citation precision; unsupported-claim rate |
| Permissions and access control | Permission fidelity; access violation rate; policy propagation latency |
| Governance and lifecycle management | Retention-policy coverage; audit response time; legal-hold completeness |
| Versioning and provenance | Provenance completeness; version recovery success; change traceability coverage |
| Workflow orchestration | Workflow completion rate; manual-touch reduction; exception backlog |
| Intelligent document processing | Field extraction F1; straight-through processing rate; human validation time |
| API-first access | API uptime; p95 API latency; developer time to first integration |
| Extensibility and integration | Extension deployment time; integration count; breaking-change frequency |
| Collaboration and review | Review turnaround time; active contributor rate; correction acceptance rate |
| Agent-safe operation | Agent task success rate; human-intervention rate; policy-violation rate |
| Observability and administration | Mean time to detect or resolve failures; job failure rate; cost per indexed or answered item |
| Scalability and performance | Indexing throughput; p95/p99 latency; maximum tested corpus size |
| Data portability and lock-in control | Export completeness; migration success rate; proprietary-dependency count |
| User and developer experience | Time to complete common task; adoption rate; developer satisfaction |
7. MVP Functional Compliance
A system can be considered compliant with the MVP interpretation of this FRS when the following P0 behavior is demonstrably implemented:
- Assets can be created, assigned stable IDs, retrieved, updated, grouped, retired, and governed through APIs.
- Baseline heterogeneous formats can be ingested and normalized into a common representation.
- Source provenance is preserved for ingested assets.
- Metadata, classification, contextual entities, and relationships can be created, queried, and updated.
- Search and filtered retrieval work across content, metadata, lifecycle state, source context, and relationships.
- Retrieval respects permissions and policy constraints.
- Transformations produce traceable derived artifacts with source lineage.
- Workflows can be executed, tracked, retried, canceled, and audited.
- Material operations produce audit events.
- Human, application, automation, and AI-agent actors are represented explicitly.
- AI agents can only act through bounded, permissioned, auditable operations.
- Structured errors and partial-failure reports are available for invalid or failed operations.
- Operators can inspect job state and perform basic recovery actions.
8. Traceability
8.1 PRD-to-FRS Coverage
| PRD Concept | FRS Coverage |
|---|---|
| Stable knowledge asset identity | FR-001–FR-010 |
| Ingestion and normalization | FR-020–FR-030 |
| Metadata, classification, and contextualization | FR-040–FR-050 |
| Search, query, and retrieval | FR-060–FR-071 |
| Traceable transformation and derived artifacts | FR-080–FR-090 |
| Workflow and job orchestration | FR-100–FR-110 |
| Permissions, governance, audit, and lifecycle | FR-120–FR-132 |
| Versioning and provenance | FR-140–FR-146 |
| Agent-safe operation | FR-160–FR-169 |
| API-first access, integration, and extensibility | FR-180–FR-188 |
| Observability and administration | FR-200–FR-207 |
| Export, portability, and migration | FR-220–FR-225 |
| Structured error handling and correctness | FR-240–FR-245 |
8.2 Corporate Use-Case Coverage
| Corporate Use Case | Most Relevant FRS Areas |
|---|---|
| Enterprise AI knowledge access and grounded assistants | Retrieval, context modeling, permissions, provenance, grounded AI workflows, agent-safe operation |
| Document-centric process automation | Ingestion, extraction, transformation, workflow, human review, audit, lifecycle |
| Governance, records, compliance, and audit readiness | Permissions, governance, lifecycle, audit, versioning, export, reporting |
| Secure content collaboration and file-service modernization | Asset identity, metadata, relationships, permissions, source references, retrieval |
| Legal and professional-services knowledge work | Contextual entities, strict permissions, provenance, relationship modeling, review, audit |
| Customer service and support knowledge | Search, classification, freshness/lifecycle state, review, grounded answers, feedback |
| Digital content supply chain and omnichannel publishing | Transformation, derived artifacts, workflow, approval, publishing adapters, export |
| Enterprise application content services | API-first access, adapters, contextual entities, relationships, workflows, events |
| R&D, engineering, technical, and project knowledge reuse | Context modeling, relationship retrieval, provenance, semantic retrieval, dependency analysis |
| Digital asset and rich-media operations | Media-derived representations, metadata, rights, renditions, rich-media retrieval |
| Corporate intranet, policy, onboarding, and team knowledge base | Search, metadata, lifecycle, review, publishing consumers, application APIs |
| Custom knowledge-backed applications | APIs, schemas, extensibility, export, provider neutrality, workflow services |
9. Acceptance Perspective
The system satisfies this FRS when:
- P0 requirements are implemented and verified through repeatable functional tests.
- Each material operation has explicit input, output, error, permission, and audit behavior.
- Assets retain stable identity across common lifecycle changes.
- Ingestion and normalization produce retrievable, contextualized, traceable assets.
- Search, retrieval, transformation, workflow, export, and agent operations enforce permissions consistently.
- Derived artifacts can be traced back to source assets and operation context.
- Workflows expose observable state, outputs, failures, retries, and audit trails.
- AI agents can operate only through explicit, bounded, reviewable, and auditable interfaces.
- Operators can inspect status, diagnose failures, and recover common operational issues.
- The system can be evaluated against the capability KPIs in this document.
10. Requirement Index
| ID | Priority | Title | Section |
|---|---|---|---|
| FR-001 | P0 | Create knowledge assets | 1 Knowledge Asset Registry and Persistence |
| FR-002 | P0 | Assign stable asset identity | 1 Knowledge Asset Registry and Persistence |
| FR-003 | P0 | Persist asset state | 1 Knowledge Asset Registry and Persistence |
| FR-004 | P0 | Retrieve assets by identifier | 1 Knowledge Asset Registry and Persistence |
| FR-005 | P0 | Update asset content and metadata | 1 Knowledge Asset Registry and Persistence |
| FR-006 | P0 | Retire or delete assets under policy | 1 Knowledge Asset Registry and Persistence |
| FR-007 | P0 | Group assets into collections | 1 Knowledge Asset Registry and Persistence |
| FR-008 | P0 | Represent original and normalized forms | 1 Knowledge Asset Registry and Persistence |
| FR-009 | P1 | Detect duplicate or repeated ingestion | 1 Knowledge Asset Registry and Persistence |
| FR-010 | P1 | Support aliases and supersession | 1 Knowledge Asset Registry and Persistence |
| FR-020 | P0 | Submit ingestion jobs | 2 Ingestion and Normalization |
| FR-021 | P0 | Ingest baseline heterogeneous formats | 2 Ingestion and Normalization |
| FR-022 | P0 | Record ingestion provenance | 2 Ingestion and Normalization |
| FR-023 | P0 | Normalize content | 2 Ingestion and Normalization |
| FR-024 | P0 | Extract structural elements | 2 Ingestion and Normalization |
| FR-025 | P0 | Expose ingestion status and failures | 2 Ingestion and Normalization |
| FR-026 | P1 | Support incremental re-ingestion | 2 Ingestion and Normalization |
| FR-027 | P1 | Support pluggable extractors and connectors | 2 Ingestion and Normalization |
| FR-028 | P1 | Validate ingestion output | 2 Ingestion and Normalization |
| FR-029 | P2 | Support advanced OCR and layout extraction | 2 Ingestion and Normalization |
| FR-030 | P2 | Support media-derived representations | 2 Ingestion and Normalization |
| FR-040 | P0 | Manage explicit metadata | 3 Metadata, Classification, and Context Modeling |
| FR-041 | P0 | Support standard metadata fields | 3 Metadata, Classification, and Context Modeling |
| FR-042 | P0 | Support custom metadata schemas | 3 Metadata, Classification, and Context Modeling |
| FR-043 | P0 | Assign classifications | 3 Metadata, Classification, and Context Modeling |
| FR-044 | P0 | Define relationships between assets | 3 Metadata, Classification, and Context Modeling |
| FR-045 | P0 | Represent contextual entities | 3 Metadata, Classification, and Context Modeling |
| FR-046 | P0 | Query context | 3 Metadata, Classification, and Context Modeling |
| FR-047 | P1 | Maintain relationship semantics | 3 Metadata, Classification, and Context Modeling |
| FR-048 | P1 | Support inferred metadata review | 3 Metadata, Classification, and Context Modeling |
| FR-049 | P1 | Validate metadata against schemas | 3 Metadata, Classification, and Context Modeling |
| FR-050 | P2 | Support domain-specific context packages | 3 Metadata, Classification, and Context Modeling |
| FR-060 | P0 | Retrieve by asset ID | 4 Search, Query, and Retrieval |
| FR-061 | P0 | Search by text | 4 Search, Query, and Retrieval |
| FR-062 | P0 | Filter by metadata and lifecycle state | 4 Search, Query, and Retrieval |
| FR-063 | P0 | Retrieve by relationship and context | 4 Search, Query, and Retrieval |
| FR-064 | P0 | Return source-grounded result data | 4 Search, Query, and Retrieval |
| FR-065 | P0 | Enforce permission-aware retrieval | 4 Search, Query, and Retrieval |
| FR-066 | P0 | Support stable pagination and sorting | 4 Search, Query, and Retrieval |
| FR-067 | P1 | Support facets and aggregations | 4 Search, Query, and Retrieval |
| FR-068 | P1 | Support semantic retrieval | 4 Search, Query, and Retrieval |
| FR-069 | P1 | Support grounded answer retrieval | 4 Search, Query, and Retrieval |
| FR-070 | P1 | Capture retrieval feedback | 4 Search, Query, and Retrieval |
| FR-071 | P2 | Support federated query patterns | 4 Search, Query, and Retrieval |
| FR-080 | P0 | Execute transformations | 5 Transformation, Composition, and Derived Artifacts |
| FR-081 | P0 | Compose outputs from multiple assets | 5 Transformation, Composition, and Derived Artifacts |
| FR-082 | P0 | Persist derived artifacts | 5 Transformation, Composition, and Derived Artifacts |
| FR-083 | P0 | Record transformation lineage | 5 Transformation, Composition, and Derived Artifacts |
| FR-084 | P0 | Support parameterized transformations | 5 Transformation, Composition, and Derived Artifacts |
| FR-085 | P0 | Enforce transformation permissions | 5 Transformation, Composition, and Derived Artifacts |
| FR-086 | P1 | Support human review for transformations | 5 Transformation, Composition, and Derived Artifacts |
| FR-087 | P1 | Support controlled re-runs | 5 Transformation, Composition, and Derived Artifacts |
| FR-088 | P1 | Compare derived artifacts | 5 Transformation, Composition, and Derived Artifacts |
| FR-089 | P2 | Publish transformation outputs | 5 Transformation, Composition, and Derived Artifacts |
| FR-090 | P2 | Support reusable transformation templates | 5 Transformation, Composition, and Derived Artifacts |
| FR-100 | P0 | Define workflow templates | 6 Workflow and Job Orchestration |
| FR-101 | P0 | Execute workflows | 6 Workflow and Job Orchestration |
| FR-102 | P0 | Track workflow state | 6 Workflow and Job Orchestration |
| FR-103 | P0 | Respect step dependencies | 6 Workflow and Job Orchestration |
| FR-104 | P0 | Return workflow results | 6 Workflow and Job Orchestration |
| FR-105 | P0 | Retry, resume, and cancel jobs | 6 Workflow and Job Orchestration |
| FR-106 | P0 | Audit workflow operations | 6 Workflow and Job Orchestration |
| FR-107 | P1 | Support event and schedule triggers | 6 Workflow and Job Orchestration |
| FR-108 | P1 | Support human tasks | 6 Workflow and Job Orchestration |
| FR-109 | P1 | Maintain exception queues | 6 Workflow and Job Orchestration |
| FR-110 | P2 | Support cross-system orchestration | 6 Workflow and Job Orchestration |
| FR-120 | P0 | Represent actors | 7 Permissions, Governance, Audit, and Lifecycle |
| FR-121 | P0 | Authorize operations | 7 Permissions, Governance, Audit, and Lifecycle |
| FR-122 | P0 | Enforce sensitivity and lifecycle constraints | 7 Permissions, Governance, Audit, and Lifecycle |
| FR-123 | P0 | Preserve source permissions where available | 7 Permissions, Governance, Audit, and Lifecycle |
| FR-124 | P0 | Audit material operations | 7 Permissions, Governance, Audit, and Lifecycle |
| FR-125 | P0 | Query audit history | 7 Permissions, Governance, Audit, and Lifecycle |
| FR-126 | P0 | Fail closed on ambiguous access | 7 Permissions, Governance, Audit, and Lifecycle |
| FR-127 | P1 | Manage retention policies | 7 Permissions, Governance, Audit, and Lifecycle |
| FR-128 | P1 | Support legal hold | 7 Permissions, Governance, Audit, and Lifecycle |
| FR-129 | P1 | Support archival and defensible deletion | 7 Permissions, Governance, Audit, and Lifecycle |
| FR-130 | P1 | Synchronize permission changes | 7 Permissions, Governance, Audit, and Lifecycle |
| FR-131 | P1 | Produce governance reports | 7 Permissions, Governance, Audit, and Lifecycle |
| FR-132 | P2 | Integrate with external policy and DLP systems | 7 Permissions, Governance, Audit, and Lifecycle |
| FR-140 | P1 | Version asset content | 8 Versioning and Provenance |
| FR-141 | P1 | Version metadata and relationships | 8 Versioning and Provenance |
| FR-142 | P1 | Compare and restore versions | 8 Versioning and Provenance |
| FR-143 | P0 | Expose source provenance | 8 Versioning and Provenance |
| FR-144 | P0 | Expose derived-artifact lineage | 8 Versioning and Provenance |
| FR-145 | P1 | Support dependency impact analysis | 8 Versioning and Provenance |
| FR-146 | P2 | Support provenance graph traversal | 8 Versioning and Provenance |
| FR-160 | P0 | Register AI agents as explicit actors | 9 Agent-Safe AI Interaction |
| FR-161 | P0 | Expose a bounded operation catalog | 9 Agent-Safe AI Interaction |
| FR-162 | P0 | Apply permissions to agent operations | 9 Agent-Safe AI Interaction |
| FR-163 | P0 | Provide context packages | 9 Agent-Safe AI Interaction |
| FR-164 | P0 | Audit agent operations | 9 Agent-Safe AI Interaction |
| FR-165 | P0 | Require review gates where policy demands | 9 Agent-Safe AI Interaction |
| FR-166 | P1 | Support grounded AI answer workflows | 9 Agent-Safe AI Interaction |
| FR-167 | P1 | Remain provider neutral | 9 Agent-Safe AI Interaction |
| FR-168 | P1 | Constrain agent tasks | 9 Agent-Safe AI Interaction |
| FR-169 | P2 | Support multi-step agent workflows | 9 Agent-Safe AI Interaction |
| FR-180 | P0 | Provide service APIs | 10 API, Integration, and Extensibility |
| FR-181 | P0 | Provide stable programmatic contracts | 10 API, Integration, and Extensibility |
| FR-182 | P0 | Accept external processing results | 10 API, Integration, and Extensibility |
| FR-183 | P1 | Support source adapters | 10 API, Integration, and Extensibility |
| FR-184 | P1 | Emit events and webhooks | 10 API, Integration, and Extensibility |
| FR-185 | P1 | Support extensible schemas and plugins | 10 API, Integration, and Extensibility |
| FR-186 | P1 | Abstract implementation backends | 10 API, Integration, and Extensibility |
| FR-187 | P1 | Version APIs | 10 API, Integration, and Extensibility |
| FR-188 | P2 | Support extension registry patterns | 10 API, Integration, and Extensibility |
| FR-200 | P0 | Expose job and ingestion status | 11 Observability and Administration |
| FR-201 | P0 | Return correlation identifiers | 11 Observability and Administration |
| FR-202 | P0 | Support administrative recovery actions | 11 Observability and Administration |
| FR-203 | P1 | Expose operational metrics | 11 Observability and Administration |
| FR-204 | P1 | Expose retrieval quality signals | 11 Observability and Administration |
| FR-205 | P1 | Expose AI operation and cost signals | 11 Observability and Administration |
| FR-206 | P1 | Support governance inspection | 11 Observability and Administration |
| FR-207 | P2 | Support policy simulation | 11 Observability and Administration |
| FR-220 | P1 | Export asset packages | 12 Export, Portability, and Migration |
| FR-221 | P1 | Export by scope | 12 Export, Portability, and Migration |
| FR-222 | P1 | Include manifests and integrity data | 12 Export, Portability, and Migration |
| FR-223 | P1 | Support re-import or migration validation | 12 Export, Portability, and Migration |
| FR-224 | P2 | Support long-term archival formats | 12 Export, Portability, and Migration |
| FR-225 | P2 | Produce migration reports | 12 Export, Portability, and Migration |
| FR-240 | P0 | Return structured errors | 13 Error Handling and Functional Correctness |
| FR-241 | P0 | Avoid silent failures | 13 Error Handling and Functional Correctness |
| FR-242 | P0 | Validate inputs | 13 Error Handling and Functional Correctness |
| FR-243 | P0 | Report partial failures | 13 Error Handling and Functional Correctness |
| FR-244 | P1 | Support idempotency | 13 Error Handling and Functional Correctness |
| FR-245 | P1 | Support conflict detection | 13 Error Handling and Functional Correctness |
11. Open Functional Decisions
The following decisions should be resolved during architecture and implementation planning:
- Asset identity strategy: UUID, content fingerprint, source-derived ID, hybrid identity, or pluggable resolver.
- Source-of-truth strategy for permissions: engine-owned, source-synchronized, delegated, or hybrid.
- Minimum baseline format set for MVP and required extraction depth per format.
- Versioning model for content, metadata, relationships, derived artifacts, and workflow state.
- Workflow execution model: embedded engine, external orchestrator, or adapter-based hybrid.
- Search architecture: lexical only for MVP, semantic retrieval in V1, or combined retrieval from the start.
- Provenance storage model: relational, event-sourced, graph-backed, or hybrid.
- Export package format and schema versioning policy.
- Extension boundary for source connectors, transformation modules, policy modules, and AI/model adapters.
- Human review model: built-in review primitives only, external task system integration, or both.
12. Stability Note
Changes to this FRS should be treated as deliberate changes to externally observable product behavior. Implementation details may change independently, but requirements related to identity, provenance, permission enforcement, auditability, traceable transformation, and agent-safe operation should remain stable unless the product scope is intentionally revised.