Hospital-grade Agent OS with native FHIR/HL7v2, clinical intelligence, and healthcare compliance.
From silicon to sentient systems. Two engines — AI Compute Center EPC and the CORA Enterprise AI Operating System — give your company one central brain, Axion, and a governed synapse for every employee, Synapse. Compliant, auditable, reversible.
From GPU clusters and liquid cooling to agent operations, compliance auditing, and knowledge graphs — one vendor, one stack.
Most enterprises adopt AI by letting each department buy its own tool. CORA inverts that: first stand up one central brain that remembers, reasons, and takes responsibility — then deliver its capability to every employee through a governed synapse.
OpenClaw, Hermes Agent, NVIDIA NemoClaw are great — until you put them in enterprise production. The gap isn't the LLM. It's the OS layer around it.
| Dimension | CORA | NVIDIA NemoClaw | OpenClaw | Hermes Agent |
|---|---|---|---|---|
| Compliance framework | ✓ ISO/GDPR/HIPAA/EU AI Act | — | — | — |
| 4-stage prevention | ✓ Industry-first | Containment sandbox | — | — |
| Two-person approval | ✓ Single-use grant · args-bound | — | — | — |
| Post-execution verification | ✓ Unverified ≠ success | — | — | — |
| Proposal sandbox & rollback | ✓ Preview → review → merge → roll back | — | — | — |
| Unified enterprise memory | ✓ 5 stores, 1 recall + provenance | — | Local memory | Local memory |
| Object & action ontology | ✓ Object types + action types | — | — | — |
| Field-level masking | ✓ Withheld — and said to be withheld | — | — | — |
| Audit depth | ✓ 22 auto modules × 4 industries | Structured logs | — | — |
| Multi-tenant isolation | ✓ Instance + Tenant | Single sandbox | — | — |
| SaaS billing engine | ✓ 4 tiers + metering | — | — | — |
| Air-Gap offline deploy | ✓ SQLite + Ollama | Partial | — | — |
Most platforms let the LLM run first and intervene after something goes wrong. CORA moves the control point upstream of execution — the decisive criterion in audit and security sign-off, and the line that separates a proof-of-concept from an enterprise-wide deployment.
Intent screening · injection defense
Unified ACL · zero-trust gateway
Egress control · field-level masking
Global audit · post-exec verify
Flagship, expansion, technical POC, and service bundles — each tier deploys on its own, or stacks into a full Agentic OS.
Hospital-grade Agent OS with native FHIR/HL7v2, clinical intelligence, and healthcare compliance.
Turns existing ERP / WMS / CRM into a conversational interface — proactive alerts, forecasts, delegations.
Hourly runtime checks across ISO 27001 / 42001 / 27701 / 22301 / 9001 with auto-evidence.
A guardrail in front of any LLM: injection defense, PII masking, egress control, zero-trust tool execution.
Native Oracle / MSSQL / trad-simp Chinese, on-prem deploy, national-grade compliance.
Cuts LLM spend 30–60% while improving reliability.
Deeper than RAG: employees, customers, orders, projects, and documents are objects in one ontology — five stores recalled at once, each answer carrying its provenance.
Run the decision before you make it — new processes, new org structures, new pricing — with every proposal stating a measurable expected outcome up front.
The full Agentic OS — effectively an AI-era SAP for your company.
Forward Deployed Engineers on-site 4–12 weeks, tuning CORA to the customer's shape.
Preset packs for manufacturing, retail, services, finance, healthcare. Live in 2 weeks.
An AI coding assistant for IT / DevOps, running in a controlled PTY sandbox with opaque branding.
CORA isn't a tool. It's the full runtime for enterprise AI. Four engines make up the Axion brain, the fifth delivers it to every employee, and the sixth enforces compliance at runtime.
The brain's runtime: state-machine orchestration plus a zero-trust tool gateway, routing each task to the right model (OpenAI / Claude / Gemini / local) by complexity. Every thought and tool call is traceable and replayable.
Relational, vector, graph (Apache AGE), time-series, and object stores — one recall, one result set. Every memory states which store and which moment it came from, and a store that didn't answer is reported as such.
Your nouns and verbs, written down as definitions the system understands: customer, work order, and contract are objects; approve, invoice, and dispatch are actions — each with preconditions, arguments, and a way to verify it. The AI works in business language, not table schemas.
Foresight → proposal → internal review → scorecard. Run the boardroom scenario ("what if materials rise 20% next year"), with every proposal stating a measurable expectation up front — then checked against reality afterwards, and marked as missed when it misses.
One governed agent per employee: bound to that person's identity, sharing the same brain, disabled individually or in cascade, with a master kill switch. Agents collaborating exchange object references, never a dump of the data.
ISO 27001 / 42001 / 27701 / 22301 / 9001 modules on an hourly automated sweep — with four-stage prevention, two-person approval, field-level masking, and Instance + Tenant isolation, all enforced at runtime.
Every CORA deployment is owned by an FDE squad. Not consultants — engineers who write the code, redesign the process, and sit on your floor.