Move the intelligence to the data
Most AI platforms assume the data can come to the model: a stable network, a cloud region, unlimited bandwidth. The environments our clients operate in — city streets, forward positions, clinical settings, courtrooms of evidence — rarely cooperate. Enkidu builds distributed edge AI platforms that move the intelligence to the data instead: self-contained edge nodes that sense, infer, and decide locally, joined in a self-healing mesh, and coordinated by a single central node that owns the committed picture.
Models propose; a deterministic adjudication engine — never a model — commits the operator-facing result. That is what makes an Enkidu edge platform fast, explainable, and defensible in front of an auditor, a regulator, or a commander.
- Deployable, ruggedised edge nodes
- Self-healing mesh & reachback fabric
- Adaptive, custody-tracked sensor ingestion
- Explainable outputs with a full trace tree
- Tangram + Origi governance built in
One pattern, four proving grounds
Distributed intelligence-fusion at the tactical edge — from dismounted teams to autonomous platforms, surviving network loss and reconciling upward.
Northwind →Ambient urban-sensing fabrics for utilities, transport, environmental and emergency agencies — with a civilian privacy framework enforced at every share.
Lamassu →Hospital-connected smart health units — clinical-grade sensing, real-time AI triage flags, and live telehealth at the point of need, escalation designed in.
MedBooth →Evidence-handling and analysis environments where chain of custody, provenance, and reproducibility are not features but requirements.
ECCC case study →