{
  "artifact": "institutional-intelligence-landscape",
  "version": "1.0",
  "as_of": "2026-07-18",
  "target_count": 100,
  "scoring": {
    "scale": "0-5",
    "anchors": {
      "0": "Absent / not applicable",
      "1": "Minimal or incidental",
      "2": "Partial / emerging",
      "3": "Solid, core-adjacent capability",
      "4": "Strong / differentiated",
      "5": "Category-defining / best-in-class"
    },
    "note": "Evidence-informed analyst judgements, not vendor-audited. Each score justified by a cited source. Re-scored as evidence improves."
  },
  "dimensions": [
    {"key": "ka", "name": "Knowledge acquisition", "def": "Ingesting diverse real-world sources (docs, feeds, filings, papers)"},
    {"key": "kg", "name": "Knowledge graph", "def": "Entities + relationships as a queryable graph"},
    {"key": "ont", "name": "Ontology", "def": "Explicit, evolvable semantic model"},
    {"key": "evs", "name": "Evidence scoring", "def": "Rating the strength/quality of evidence"},
    {"key": "prov", "name": "Provenance", "def": "Every conclusion traceable to its sources"},
    {"key": "rw", "name": "Research workflow", "def": "Structured plan-retrieve-synthesize-cite"},
    {"key": "ds", "name": "Decision support", "def": "Producing decisions / recommendations"},
    {"key": "pol", "name": "Policy intelligence", "def": "Legislative / regulatory tracking + analysis"},
    {"key": "ot", "name": "Outcome tracking", "def": "Measuring what happened after a decision"},
    {"key": "ll", "name": "Learning loops", "def": "System improves from outcomes over time"},
    {"key": "cd", "name": "Cross-domain capability", "def": "Works across multiple domains, not one vertical"},
    {"key": "hg", "name": "Human governance", "def": "Review gates, oversight, auditable control"}
  ],
  "organizations": [
    {
      "id": "palantir",
      "name": "Palantir (Foundry + AIP)",
      "category": "Enterprise Ontology / Decision OS",
      "day": 1,
      "vision": "An ontology-powered operating system that turns enterprise data into governed decisions and actions.",
      "customers": "Government, defense, and large enterprises (manufacturing, health, finance).",
      "differentiator": "The Ontology as a live operational semantic layer, fused with action/decision orchestration, deep lineage and rigorous governance.",
      "weaknesses": "Models operational enterprise reality, not open cross-domain human knowledge, scientific evidence, or policy; closed and costly; no evidence-scoring or research-synthesis loop.",
      "scores": {"ka": 4, "kg": 5, "ont": 5, "evs": 1, "prov": 5, "rw": 2, "ds": 5, "pol": 1, "ot": 3, "ll": 2, "cd": 4, "hg": 5},
      "sources": [
        "https://www.palantir.com/platforms/foundry/",
        "https://www.palantir.com/docs/foundry/ontology/overview",
        "https://www.palantir.com/docs/foundry/announcements/release-notes"
      ]
    },
    {
      "id": "quantexa",
      "name": "Quantexa",
      "category": "Decision Intelligence / Contextual KG",
      "day": 1,
      "vision": "Put context behind every decision via a trusted, connected data foundation.",
      "customers": "Banks, insurers, and government - fraud, AML, credit, risk, compliance.",
      "differentiator": "Best-in-class entity resolution feeding a contextual knowledge graph, closing into human + AI decisioning.",
      "weaknesses": "Anchored in financial-services risk/fraud; ontology narrower than Palantir; no policy, evidence-scoring, or open-knowledge research.",
      "scores": {"ka": 4, "kg": 5, "ont": 3, "evs": 2, "prov": 4, "rw": 3, "ds": 4, "pol": 1, "ot": 3, "ll": 3, "cd": 3, "hg": 3},
      "sources": [
        "https://www.quantexa.com/platform/decision-intelligence-platform/",
        "https://www.quantexa.com/platform/graph-analytics/",
        "https://www.globenewswire.com/news-release/2025/03/06/3038527/0/en/Quantexa-Unleashes-Wave-of-Next-Gen-AI-Decision-Intelligence-at-QuanCon25.html"
      ]
    },
    {
      "id": "fiscalnote",
      "name": "FiscalNote (PolicyNote)",
      "category": "Policy Intelligence",
      "day": 1,
      "vision": "AI-driven policy & regulatory intelligence - be the authoritative source of what's changing.",
      "customers": "Government-affairs, public-affairs and enterprise policy/regulatory teams.",
      "differentiator": "The broadest primary-source legislative/regulatory coverage (Congress, 50 states, 100+ countries, 12k municipalities), now exposed to agents via an MCP API.",
      "weaknesses": "Monitoring & retrieval, not decision-learning: no knowledge graph, ontology, evidence scoring, or outcome/learning loop.",
      "scores": {"ka": 5, "kg": 1, "ont": 1, "evs": 1, "prov": 4, "rw": 3, "ds": 2, "pol": 5, "ot": 1, "ll": 1, "cd": 2, "hg": 2},
      "sources": [
        "https://fiscalnote.com/products/policynote",
        "https://fiscalnote.com/newsroom/fiscalnote-launches-policynote-mcp-in-the-openai-app-store-significantly-expanding-access-to-its-policy-intelligence",
        "https://www.businesswire.com/news/home/20260519794481/en/FiscalNote-Expands-PolicyNote-API-Adding-Local-Government-Intelligence-to-Enterprise-and-AI-Agent-Workflows"
      ]
    },
    {
      "id": "relationalai",
      "name": "RelationalAI",
      "category": "Knowledge Graph / Reasoning Infra",
      "day": 1,
      "vision": "A relational knowledge-graph coprocessor giving AI agents the reasoning to make smarter decisions - inside the data cloud.",
      "customers": "Snowflake enterprises; data & AI platform teams.",
      "differentiator": "Embedded KG + rules/graph/predictive/prescriptive reasoners over one semantic foundation; OSI interop lets it import existing (even Palantir) ontologies.",
      "weaknesses": "Infrastructure, not an application: no external knowledge acquisition, policy, evidence scoring, outcome tracking, or research workflow out of the box.",
      "scores": {"ka": 2, "kg": 5, "ont": 4, "evs": 1, "prov": 3, "rw": 2, "ds": 4, "pol": 0, "ot": 1, "ll": 2, "cd": 3, "hg": 3},
      "sources": [
        "https://www.relational.ai/post/relationalai-knowledge-graph-coprocessor-is-generally-available-as-a-snowflake-native-app",
        "https://www.globenewswire.com/news-release/2026/06/02/3305546/0/en/RelationalAI-Closes-the-AI-Value-Gap-with-New-Agentic-Decision-Intelligence-Capabilities-for-the-Snowflake-AI-Data-Cloud.html",
        "https://venturebeat.com/ai/relationalai-launches-powerful-knowledge-graph-coprocessor-for-snowflake-users"
      ]
    },
    {
      "id": "sas-viya",
      "name": "SAS (Viya)",
      "category": "Decision Intelligence / Analytics + Governance",
      "day": 1,
      "vision": "Own the full decision life cycle - model, orchestrate, monitor, govern.",
      "customers": "Regulated industries: banking, insurance, healthcare, government.",
      "differentiator": "Breadth across the decision life cycle plus mature model governance, explainability and audit; named a Leader in the inaugural 2026 Gartner MQ for Decision Intelligence Platforms.",
      "weaknesses": "Analytics/model-centric - light on knowledge graph, ontology and policy; 'learning' is model monitoring, not institutional decision memory.",
      "scores": {"ka": 3, "kg": 2, "ont": 2, "evs": 2, "prov": 4, "rw": 2, "ds": 5, "pol": 1, "ot": 4, "ll": 3, "cd": 4, "hg": 4},
      "sources": [
        "https://www.sas.com/en_us/news/press-releases/2026/february/gartner-decision-intelligence-platforms.html",
        "https://www.sas.com/en_us/software/intelligent-decisioning.html",
        "https://www.prnewswire.com/news-releases/sas-expands-sas-viya-with-governed-ai-assistants-and-agentic-ai-capabilities-302755495.html"
      ]
    }
  ],
  "day1_finding": "Across these 5, strength clusters in the front half of the loop (knowledge graph, ontology, provenance, decision support). The back half is consistently thin: Evidence scoring, Learning loops, and Research workflow are weak across every player - the whitespace the vision targets. Caveat: n=5; treat as a hypothesis to keep testing as the sample grows."
}