An enterprise data platform that turns fragmented data into a governed, executable model of operational reality — then helps you decide what to do and verifies what happened.
An enterprise data platform that turns fragmented data into a governed, executable model of operational reality — then helps you decide what to do and verifies what happened.
Most platforms show you what happened. Lugh-E models what is happening, simulates what could happen, recommends what to do, authorizes the action, and verifies the outcome. The full loop — not just the dashboard.
Your data is not tables — it is entities with properties, relationships, behaviors, and lifecycles. Lugh-E models data the way your business works, not the way a relational database stores it.
Every action — from recommendation to authorization to execution to verification — is policy-gated, audited, and replayable. No autonomous decisions without human accountability.
Fuse sensor data, tracks, maps, and intelligence into one operational picture. For defense, industrial, and mission-critical environments where seeing the full picture is not optional.
Every operation is replayable with byte-identical results. Corrections and retractions are first-class. Compliance and after-action review are built in, not bolted on.
Lawful authority binding, human command responsibility, evidence sufficiency gates, and ethics board policy bundles — mandatory parts of the platform, not optional add-ons. Air-gapped deployment for classified networks.
Most data platforms stop at dashboards. They show you what happened — a metric spiked, a shipment was delayed, a sensor went out of range. What they do not show you is why it happened, what you should do about it, whether your action is authorized, and whether it worked. Lugh-E closes that loop.
Lugh-E is an object-centric data platform that models your operational reality — entities, relationships, environments, scenarios — and lets you simulate, decide, act, and verify within one governed system. It is what Palantir Foundry would be if it went beyond passive analytics into an action platform with deterministic replay, sensor fusion, and governed authorization.
Lugh-E models your operational reality as objects — entities with typed properties, relationships, behaviors, and lifecycles. Not tables, not documents — objects. A supply chain is not a join between five tables; it is a graph of suppliers, parts, shipments, and customers with relationships that have meaning.
The ontology engine manages types, schema evolution, compatibility checking, and migration planning. When your business model changes, the ontology adapts — and every downstream query, simulation, and dashboard reflects the change automatically.
An ontology engine that manages types, properties, relationships, inheritance, behaviors, constraints, and validation rules. When your business model changes, the ontology evolves — and every downstream query, simulation, and dashboard reflects the change. Schema evolution with compatibility checking and migration planning, not a scary ALTER TABLE that breaks every dashboard.
Lugh-EQL queries across relational, graph, vector, tensor, temporal, geospatial, epistemic, and simulation representations in one statement. Find customers similar to Customer X who are connected to Company Y in the graph, and show their purchase history from the last 30 days, with geospatial context — one query, one result, no ETL pipeline.
Query across graphs, vectors, time-series, and simulation state in one language. No switching between SQL, Cypher, and a vector API. One query, one result, one consistent view — with epistemic awareness built in.
See the operational picture, simulate alternatives, authorize an action through policy gates, and verify the outcome — all in one platform with full governance and deterministic replay for after-action review.
Replay any decision at any point in the past. See what the system saw, what it recommended, what was authorized, and what happened — with byte-identical deterministic replay and tamper-evident audit trails.
Fuse sensor data into an operational picture at the edge — even without connectivity. Track management, hypothesis management, and contradiction detection for mission-critical decisions where the disagreement is the information.
When three sensors report a moving object, Lugh-E fuses the observations into a single track with position, velocity, and uncertainty. When tracks cross, the system maintains hypothesis management — it does not arbitrarily merge or split tracks without evidence. When a track is lost, the system predicts where it should be and searches for it.
A 24-state lifecycle governs every action from draft to verified. Draft, proposed, evidence-bound, simulation-pending, simulated, authorization-pending, authorized, denied, published, handoff-pending, owner-accepted, executing, outcome-pending, verified, diverged, mitigation-pending, mitigated, revoked, cancelled, expired. Every transition requires evidence, policy approval, and human accountability.
No action reaches execution without passing through authorization — and no authorization is autonomous. A human is always in the loop, bound to lawful authority and the exact version of the proposal that was approved.
Run Lugh-E on your own infrastructure — bare metal, VM, or Kubernetes. Or use the managed cloud — we run it, you use it. Or hybrid — keep sensitive data on-prem, use managed for non-sensitive. The same identity, the same governance, the same audit trail across both.
Generated, type-safe SDKs in Rust, TypeScript, Python, Go, and Java — all exposing the same 130 operations across 14 families. Protobuf-first with exact JSON/REST parity. GraphQL for read-only queries. WebSocket for subscriptions. Your developers use the language they know — not a proprietary DSL.
Actions flow from draft to verified. Most actions complete the full cycle — some diverge and require mitigation. Every state transition is policy-gated, audited, and replayable.
No action reaches execution without evidence, authorization, and simulation. No action closes without verification. The lifecycle is the audit trail.
130 operations across 14 families — from ontology management to sensor fusion to governed action. Each family is a first-class API surface with type-safe SDKs in five languages.
Your developers call the same operations whether they are building a planning tool, a sensor dashboard, or a mission commander. One API. One ontology. One governance model.
The data platform industry sells dashboards. Beautiful, interactive, real-time dashboards that show you what happened — after it happened. A metric spiked. A shipment was delayed. A sensor went out of range. The dashboard shows the spike. It does not show why. It does not recommend what to do. It does not authorize the action. It does not verify the outcome. It does not learn from the result. It shows you a chart, and you figure out the rest.
Lugh-E takes a different position. Data without action is noise. A metric spike without a recommendation is a distraction. A recommendation without authorization is a liability. An action without verification is a gamble. Lugh-E closes the loop — model, interpret, simulate, recommend, authorize, execute, observe, verify, learn. Every step is policy-gated, audited, and replayable. Every action has a human accountable for it. Every outcome is verified against the prediction that justified it.
That is what Lugh-E is. Not another dashboard. An action platform that turns data into decisions and decisions into verified outcomes.
Operator relevance: A mission commander can see the operational picture, simulate alternatives, authorize an action through policy gates, and verify the outcome — all in one platform with full audit trail.