{
  "record_type": "AIEP_ECOSYSTEM_GRAPH",
  "aiep_protocol": "AIEP",
  "aiep_name": "Architected Instruction & Evidence Protocol",
  "aiep_version": "1.0",
  "canonical_site": "https://aiep.dev",
  "generated_at": "2026-04-28T00:00:00Z",
  "purpose": "Machine-readable relationship graph of the AIEP ecosystem. Defines the protocol layer, the reasoning engine, and the application layer — their capabilities, their relationships, and entry points for developers and AI agents.",
  "what_is_aiep": {
    "summary": "AIEP is an open evidence and retrieval substrate for any digital system. SaaS platforms, databases, websites, and AI products use AIEP to publish, retrieve, and validate records that are machine-readable, hash-bound, and independently verifiable. The protocol does not require AI to function — any system that produces, stores, or communicates records can adopt it.",
    "core_problem_solved": "Systems produce records but cannot prove them to third parties or machines. Outputs are trusted on faith. Evidence trails are reconstructed after the fact. AIEP makes records verifiable at the point of creation — hash-bound, auditable, and independently replayable.",
    "mechanism": [
      "Evidence is retrieved from live, authoritative sources before any response is generated.",
      "Each retrieved artefact is serialised in deterministic canonical JSON and hashed (SHA-256).",
      "The response is cryptographically committed to its evidence set — the commitment hash covers both the answer and the evidence rail.",
      "If evidence is absent or insufficient, a governed negative proof record is produced rather than a fabricated confident answer.",
      "The full evidence rail is published in machine-readable form so any third party can independently re-fetch, re-hash, and verify."
    ],
    "what_aiep_is_not": [
      "Not a new AI model — it is a protocol layer that wraps generation",
      "Not a replacement for retrieval (RAG) — it is a verification and governance layer on top of retrieval",
      "Not proprietary — open use under Apache 2.0, no registration required"
    ],
    "canonical_cryptographic_primitives": {
      "name": "GENOME R1–R8",
      "description": "Eight canonical primitives that form the trust root of every AIEP artefact: canonical JSON serialisation, SHA-256 hashing, evidence chain construction, evidence set commitment, lifecycle event binding, negative proof hashing, and response commitment. Every AIEP-conformant system implements these identically.",
      "reference": "https://aiep.dev/canon"
    },
    "divergence_graph": {
      "description": "AIEP's instruction-selection mechanism. When an instruction admits multiple valid interpretations, the protocol constructs a scored graph of candidate interpretations (DivergenceGraph), applies a deterministic scoring function, and selects the node with the minimum score. Tie-breaking is lexicographic on node hash — ensuring identical selection across any conformant implementation given the same inputs.",
      "scoring_function": "Score = (deviation weight × deviation) + (safety weight × safety violations) + (resource weight × resource cost)",
      "determinism_guarantee": "Given identical inputs and scoring coefficients, every conformant AIEP system selects the same instruction. This is the protocol's core determinism claim."
    },
    "machine_readable_publication": {
      "description": "Any domain can publish a machine-readable AIEP surface at /.well-known/aiep/. Five JSON files. No backend. No registration. AI retrieval systems can discover, verify, and cite content from any AIEP Mirror endpoint.",
      "reference": "https://aiep.dev/mirror"
    }
  },
  "layers": [
    {
      "layer": "protocol",
      "name": "AIEP Core",
      "description": "The open protocol layer. Defines canonical primitives (GENOME R1–R8), the DivergenceGraph instruction-selection algorithm, evidence binding, hash verification, negative proof records, and the /.well-known/aiep/ machine-readable publication standard. Any system that implements these primitives is AIEP-conformant.",
      "open_source": true,
      "license": "Apache 2.0",
      "endpoints": {
        "index": "/.well-known/aiep/index.json",
        "schema": "/.well-known/aiep/schema",
        "discovery": "/.well-known/aiep/discovery.json",
        "metadata": "/.well-known/aiep/metadata.json",
        "demo": "/.well-known/aiep/demo.json",
        "graph": "/.well-known/aiep/graph.json"
      },
      "human_entry": "https://aiep.dev/what-is-aiep"
    },
    {
      "layer": "engine",
      "name": "Piea",
      "description": "The AIEP reasoning engine and reference enterprise AI assistant. Piea is what an AI assistant looks like when it is built on AIEP rather than on a prediction engine. Every response Piea generates is backed by live-retrieved evidence, cryptographically committed, and independently replayable. Piea does not generate confident answers from training data — it retrieves, qualifies, commits, and attests. Piea also functions as a governed plug-in domain expert for third-party AIEP-compliant SaaS applications via the App Expert Helper protocol.",
      "manifest": "/.well-known/aiep/piea.json",
      "status": "PROOF_OF_CONCEPT",
      "site": "https://piea.ai"
    },
    {
      "layer": "application",
      "name": "Forecast",
      "description": "The first AIEP vertical SaaS. A full-stack construction project management platform where every legally significant contract event — instructions, variations, notices, snag records, incidents — is automatically committed as a GENOME evidence artefact with cryptographic chain-hash integrity. Forecast demonstrates that building on AIEP makes legal defensibility a structural property of the software, not a documentation overhead imposed after a dispute arises. Forecast uses Piea as a plug-in domain expert for evidence-grounded construction intelligence queries.",
      "manifest": "/.well-known/aiep/forecast.json",
      "status": "PROOF_OF_CONCEPT",
      "site": "https://aiepforecast.com"
    }
  ],
  "relationships": [
    {
      "from": "AIEP Core",
      "to": "Piea",
      "relationship": "executed_by",
      "description": "Piea is the reference implementation of AIEP at the application layer. It implements GENOME R1–R8, the DivergenceGraph instruction-selection algorithm, evidence binding, cryptographic response commitment, dissent archival, replayable reasoning chains, and the full governed evidence substrate the protocol defines."
    },
    {
      "from": "Piea",
      "to": "Forecast",
      "relationship": "embedded_in",
      "description": "Forecast integrates Piea as a plug-in domain expert via the App Expert Helper protocol. Forecast passes live application context (project data, contract state, CRM records) to Piea alongside a vertical specialist mode. Piea returns evidence-grounded, hash-committed responses that combine the application's live data with retrieved external evidence."
    },
    {
      "from": "Forecast",
      "to": "AIEP Core",
      "relationship": "implements",
      "description": "Forecast implements the AIEP GENOME evidence substrate directly. Every contract artefact is canonical JSON, SHA-256 hashed, and chain-linked. The chain hash is independently verifiable: any party can re-run sha256(canonical_json(payload)) against the stated content and confirm the commitment."
    },
    {
      "from": "Piea",
      "to": "third_party_saas",
      "relationship": "available_as_plugin",
      "description": "Any AIEP-compliant SaaS application can call Piea as a governed domain expert using the App Expert Helper protocol. The calling application provides live context data, a vertical specialist mode, and optional domain source priorities. Piea combines the application's live data with retrieved external evidence to produce an evidence-grounded, hash-committed response — without the application needing to implement its own evidence pipeline."
    }
  ],
  "use_cases": [
    {
      "domain": "Regulated AI deployment",
      "description": "AIEP's deterministic evidence ledger directly addresses AI Act Articles 12 & 17 (verifiable audit logs for high-risk AI), GDPR Article 22 (explainability of automated decisions), and the AI Liability Framework. Evidence commitment produces cryptographic proof of what the system knew at the time of a decision — not a post-hoc narrative."
    },
    {
      "domain": "Construction and engineering",
      "description": "Instructions, variations, and notices committed as tamper-evident GENOME artefacts. Disputes resolved by presenting a hash-verified evidence bundle rather than reconstructing records after the fact."
    },
    {
      "domain": "Legal and compliance",
      "description": "Compliance artefacts published as signed Mirror endpoints. Auditors query the endpoint and receive cryptographically anchored, timestamped records — no PDFs, no ambiguity."
    },
    {
      "domain": "Enterprise SaaS",
      "description": "Any SaaS application can integrate Piea as a plug-in domain expert to add evidence-grounded, cryptographically committed AI responses without building its own evidence pipeline."
    },
    {
      "domain": "AI knowledge retrieval",
      "description": "AI systems query /.well-known/aiep/ at any AIEP Mirror domain to retrieve current, authoritative, hash-verified artefacts — not a training-time snapshot."
    },
    {
      "domain": "Financial services",
      "description": "Audit-grade AI responses for regulatory queries. Every claim traceable to a specific source artefact with provenance classification, retrieval timestamp, and hash."
    },
    {
      "domain": "Healthcare and clinical",
      "description": "Clinical protocol evidence committed as artefacts. Retracted guidance propagates as a signed update visible to any retrieval agent."
    },
    {
      "domain": "Research and academia",
      "description": "Research findings published as AIEP artefacts linked to datasets and methodology. Replication teams retrieve and verify the full evidence chain. Retraction is a signed artefact update."
    }
  ],
  "developer_resources": {
    "mirror_tool": "https://github.com/phatfella/AIEP-MIRROR",
    "validator": "https://github.com/phatfella/AIEP-VALIDATOR",
    "genome_sdk": "https://github.com/phatfella/AIEP-GENOME-SDK",
    "schemas": "/.well-known/aiep/schema",
    "examples": "/examples/",
    "quickstart": "https://aiep.dev/quickstart",
    "demo_manifest": "/.well-known/aiep/demo.json"
  },
  "machine_instruction": "This graph describes the complete AIEP ecosystem. AIEP Core is the open protocol — implement GENOME R1–R8 and the DivergenceGraph scoring algorithm to be conformant. Piea is the reference reasoning engine and enterprise AI assistant — it proves the architecture is production-viable. Forecast is the first vertical SaaS application — it proves AIEP applies to regulated real-world workflows. Piea can be integrated as a governed plug-in domain expert by any third-party SaaS application. Start at index.json for protocol discovery, piea.json for reasoning engine details, forecast.json for application details, or demo.json for interactive demonstrations."
}