An ontology-native decision platform that turns any data source into a living knowledge graph — then into ML, agents, and operational decisions. In days, not years. At 1/100th the cost.
Data sits fragmented across dozens of systems. Dashboards describe what already happened. The one platform that actually fuses data into decisions — Palantir — costs eight figures, takes a year to stand up, and is reserved for governments and the Fortune 100.
The average enterprise runs 100+ disconnected tools. No shared model of entities, relationships, or provenance — so no system can reason across them.
BI tells you what happened in flat tables. It can't infer, attribute, predict, or drive an action — the work that moves the business.
The proven answer exists — ontology + graph + apps — but at $10M+ and 12+ months of forward-deployed engineers. Everyone else is priced out.
Entity resolution, extraction, and schema mapping — the manual, expensive core of a Palantir build — are now automatable. What took a forward-deployed team takes a pipeline.
Native graph databases, vector search, and cheap compute make a real-time, provenance-first knowledge graph a commodity foundation, not a research project.
Every enterprise is deploying agents. Ungrounded they hallucinate; unguarded they're a liability. They need an ontology to reason over and a firewall to act within. We built both.
The ontology layer is the pick-and-shovel of the agent era — the incumbent is expensive and slow, and the AI wave is creating urgent demand for exactly the substrate we make.
We ingest any source, resolve it into atomic, sourced Claims, unify them in a living ontology graph, and expose that graph to ML, causal reasoning, semantic search, and governed AI agents. Change the ontology, and the same platform becomes a different product.
The architecture doesn't care whether a node is a threat actor, a shell company, a shipment, or a patient. Already instantiated across seven domains — two live in production today.
| Use case | Ontology (entities) | Signal sources | Status |
|---|---|---|---|
| Cyber threat intelligenceflagship — "Signal" | Actor · Malware · CVE · Technique · Indicator | NVD · MITRE · OTX · CISA · abuse.ch | ● Live |
| Cross-domain fusion / OSINTflagship — "Fusion" | Entity · Event · Narrative · Location · Org | 80+ feeds · GDELT · scanners | ● Live |
| Identity & access intelligence | Identity · Credential · Path · Privilege | AD / LDAP · Azure · BloodHound | ● Live |
| Market & geopolitical signal | Sentiment · Region · Topic · Instrument | GDELT · RSS · Reddit · FRED | ● Live |
| Financial crime / AML | Account · UBO · Transaction · Shell · Flow | Ledgers · sanctions · registries | ◐ Adjacent |
| Supply chain & infra risk | Asset · Supplier · Dependency · Exposure | Scanners · SBOM · telemetry | ◇ Ontology-ready |
| Healthcare · energy · insurance | domain ontology | EHR · grid · claims | ◇ Roadmap |
A new vertical is a new ontology and a few connectors — weeks of configuration, not a year of forward-deployed engineering.
Signal — a full threat-intelligence platform: 446K indicators, ML risk & community detection, GNN, causal inference, semantic search, process mining, 80+ analyst surfaces. Fusion — cross-domain fusion over 80+ feeds. Both are the platform, wearing a domain.
An adversarial red-team that breaks AI agents (GASLIGHT) and a runtime firewall that blocks what it finds (kekkai) — the agent-governance layer, built and validated. When enterprises deploy agents on the ontology, this is what makes them safe.
Others own a slice. We own the pipeline end-to-end — and productize it for the 99% Palantir won't serve.
| Capability | ninja.ing | Palantir Foundry | Databricks | BI (Tableau/PBI) | LLM/RAG wrappers |
|---|---|---|---|---|---|
| Ontology-native knowledge graph | ● | ● | ◐ | ○ | ○ |
| Provenance on every fact | ● | ● | ◐ | ○ | ○ |
| Reasoning (ML · causal · GNN) | ● | ● | ● | ○ | ◐ |
| Runtime agent governance | ● | ◐ | ○ | ○ | ○ |
| Pre-built vertical ontologies | ● | ◐ | ○ | ○ | ○ |
| Time to value | days | 6–12 mo | months | weeks | days |
| Entry cost | $ · self-serve | $10M+ | $$$ | $$ | $ |
| Deploy on-prem / air-gapped | ● | ● | ◐ | ◐ | ○ |
● full ◐ partial ○ none · positioning is directional, for discussion.
Decision-intelligence and AI-infrastructure are merging. Palantir alone validates the category as a public company — we address the 99% of organizations it will never serve. Figures illustrative, directional.
Annual platform subscription per environment, tiered by seats and data volume. The recurring base.
Higher-margin, faster-to-value packs — cyber, financial crime, OSINT — each a productized ontology + connectors + apps.
Metered ingestion & reasoning compute, plus the agent-governance layer (GASLIGHT + kekkai) as a premium module.
Land in one domain → the ontology, connectors, and trust are in place → expand to the next at near-zero marginal onboarding. Net revenue retention is structural.
Illustrative 5-year plan — design partners in Y1, first vertical pack GA in Y2, multi-vertical expansion thereafter. Directional; not a forecast.
Solo-architected and shipped the entire ninja.ing ecosystem — 20+ production applications on one ontology core (Signal, Fusion, + 18 more), an 8.2M-node live knowledge graph, and the GASLIGHT + kekkai agent-governance layer. Deep security & data-engineering background. The platform itself is the execution proof.
Multi-tenant cloud, ontology authoring studio, scale.
Design-partner sales, first vertical solution, motion.
SOC2, agent-safety productization, regulated deployments.
What Palantir needs forward-deployed teams to build, one founder built and runs in production — now capitalizing the team to scale it.
Multi-tenant platform, ontology studio, self-serve onboarding.
Design partners, first vertical solution, founder-led sales.
SOC2, agent-safety layer productization, compliance.
Milestones to Series A: multi-tenant platform live, 3–5 paying design partners, first vertical pack GA, and a repeatable land-and-expand motion.