Enterprise Accountable AI Architecture,
in one picture
One machine under every engagement — decode → graph → act — run on a version-controlled dynamic agent harness, by named AI agents that work like humans, with a human signing every consequential action.
15-min brief, quote in 60s
DAG builder, milestone plans
Connected graph + code graph
Versioned skills, connectors, runbooks — per tenant
The engine · one machine under every engagement
① Decode
Sub-graph by sub-graph
Infra, tooling, code, contracts, processes — each decoded exactly.
② Graph
Connected living graph
Sub-graphs connected; every value carries lineage + confidence.
③ Act
The pod ships on it
Provable parity, safe automation, grounded answers.
⬡ Dynamic Agent Harness — the compounding core
The integration layer, as code: lets agents plug into your stack, identity, and tools, and act safely inside your cloud. Every engagement commits to it; the next checks out where the last left off. Version-controlled per tenant — adopt the pod and the whole history is yours.
◎ Connected Knowledge Graph
Named AI Agents — Tier 1–4 autonomy
Persistent memory · versioned skills · signed identity — they work like teammates
Priya
Contract Analyst
Marcus
IT Ops & Incident
Maya
Customer Support
Felix
Compliance & Audit
Atlas
Data & Pipelines
Vega
Finance & Invoices
🔧 Tools
- REST / gRPC / GraphQL
- CDC / Debezium / Kafka
- MCP & A2A protocols
- Browser / RPA bridge
- Sandboxed coding
- SFTP / file connectors
⬡ 5-Layer Memory Stack
ReactFlow DAG
Event timeline
Hash-chained ledger (Ed25519)
Policy & roles
Budgets & hard-cap alerts
Parallel-run scoring
Auto-computed from the ledger
U.S. Patent 12,536,365 B1 · Deployment: SaaS · customer-VPC (BYOK) · fully in-customer / air-gapped — on a certified stack profile (Azure / AWS / GCP / self-managed).