Palantir Ontology

https://www.palantir.com/platforms/foundry/ontology/

Proprietary operational ontology — semantic objects + kinetic actions wired to microservices. Not open-standards KG; closed platform.

At a glance

Type
Operational digital twin
Tier
T1
Created
2003
Latest release
not applicable — not OSS
License
not applicable — not OSS
GitHub
not applicable — no GitHub repo
Pricing
Enterprise only
Funding
$2.46B total over 18 rounds; IPO 2020 NYSE:PLTR

Taxonomy

storage
graph
retrieval
graph-traversal
persistence
long-term
update
overwrite
unit
fact
governance
auditable
conflict
branch-and-merge

When to use

Optimised for: relationship modeling + reasoning + governance over pure vector

Anti-fit: not for purely-vector or simple-RAG use cases (graph adds setup cost)

Pros & cons

Pros

Most aggressive enterprise data ontology + agent fusion in production; backed by deep enterprise consulting muscle.

Cons

Vendor lock-in is total; pricing is enterprise-tier; minimal applicability outside large enterprise / government deployments.

Claims & capabilities

Q3 2025 U.S. commercial revenue +121% YoY driven by AIP adoption; BP saved $1B via optimized oil/gas operations; Fortune 100 CPG firm projected $100M savings in year 1; CAZ Investments processed 100x more leads at 90% time reduction; AIP Bootcamps as primary onboarding

Technical surface

API surface
searched not found
Backend storage
searched not found
Deployment
Both
Embedding model
searched not found
Multi-tenancy
Foundry tenant per customer with strong ACL classification; zero-trust architecture; dedicated FedRAMP High enclave for federal workloads
MCP
no first-party MCP adapter published as of 2026-05; community connectors may exist.
A2A
no Google A2A (Agent2Agent) integration documented as of 2026-05.
OpenTelemetry
no first-party OpenTelemetry exporter documented; standard logs/metrics typically available.

Similar systems

Other knowledge-graph platforms in the catalog, ranked by inbound references.

  • Neo4j T1

    Property graph DB with Cypher; native vector search; Aura Agent + MCP server for graph-as-memory. $100M GenAI investment in 2025.

  • Amazon Neptune Analytics T1

    Vector index on graph nodes queryable via openCypher. Mem0 integration GA 2025; Cognee integration for agentic RAG. Combines semantic recall with multi-hop traversal in one managed service.

  • AllegroGraph (Franz) T1

    RDF triple/quad store with RDFS++ / OWL reasoning. v8.4 (May 2025) added an NLQ interface.

  • Apache AGE T2

    openCypher over Postgres. Pairs with pgvector for graph + vector hybrid retrieval. Azure Database for PostgreSQL ships AGE with ai_extension LLM functions for entity extraction directly in SQL.

  • ArangoDB T1

    HybridGraphRAG combines vector search, graph traversal, full-text in one AQL query. ArangoGraphML for ML pipelines; LangChain integration.

  • Dgraph T2

    Vector indexing on any node. Google Gen AI Toolbox integration; LangChain agent orchestration.

Row last verified 2026-05-14. Catalog data is CC-BY-4.0 — see how to read this.