Cognitive agents
Task-specific, state-aware clusters that plan multi-step work, call internal APIs, and stop when the mandate says so.
Software that waits for a ticket is the old stack. Cybernecs designs AI agents, Cerebros, and sovereign infrastructure so operations run, report, and stay under a named human when the stake is high.
The shift
Enterprise tools sit idle until someone clicks. AI-native companies route work across a living graph — sales, finance, engineering, support — and execute with a mandate, not a chatbot in the corner.
Not a model wrapped in a landing page. Six layers that turn an existing organisation into an AI-native operation — with traces, approvals, and a place to run.
Task-specific, state-aware clusters that plan multi-step work, call internal APIs, and stop when the mandate says so.
Business systems designed around reasoning, retrieval, and live data — not another CRUD form on a legacy ERP.
Interfaces that read intent in plain language and assemble the next screen, instead of burying work in static menus.
The nervous system: ERPs, messaging, code, and finance telemetry connected to one reasoning kernel.
On-premise and air-gapped inference when intellectual property cannot sit on a vendor cloud.
Continuous inspection of model calls, tokens, and data leaving the perimeter — halt before leak, not after.
Sales, treasury, engineering, support, and logistics stop living in separate tabs. Cerebros maps them into one operational memory so agents reason on the same facts.
Financial, destructive, or security actions always submit a proposal. A human named in the mandate signs, or it does not run. Cerebros · On-premise.
Agents are not a demo chat. Each one has an identity, a memory horizon, and an approval gate. The interesting part is what they are allowed to do without asking — and what they must never do alone.
Open the identity cards · machine-readable at /.well-known/agent.json
Daily priorities, exec memos, bottleneck risks. Gate: Directors.
Outbound intent, architectural proposals, follow-ups. Gate: Sales lead.
Refactors, tests, sovereign staging. Gate: CTO escrow.
Outbound model calls, hashes, leak halt. Gate: Zero-trust.
We observe the real operation first. Then we model, connect, and deploy agents with bounded autonomy. Automation comes after the mandate is signed — not before.
APIs, inboxes, ledgers, and the exceptions people handle by phone.
A sovereign knowledge graph you can simulate before you touch production.
Tokens, retrieval, and policy gates. Nothing leaves without a trace.
Purpose-built agents with a written mandate and a named human on the gate.
Routing, analysis, and drafts run continuously. Exceptions stay human.
Agents refine from telemetry. Policy and HITL stay in the loop.
Six crawlable pages, one intent each. Same facts as the identity cards — no stuffing, no invented ROI.
Task-specific agents with a mandate and a named gate — not a chatbot in the corner.
Sovereign and air-gapped runtimes when prompts cannot leave your perimeter.
The organisation graph agents share — sales, treasury, engineering, support.
Citable answers for Google, Perplexity, and operators who need the never-line first.
Headquarters and research in Paris. Delivery in London, USA, China, Africa.
COS-01, REV-09, DEV-44, AUD-88 — plus machine JSON at /.well-known/agent.json.
Hospitality, freight, and industrial operations — places where a wrong price, a missed slot, or a leaked document actually costs money. We design the system; we do not invent client percentages on this page.
Replace fragmented booking desks with a private agent that reads inventory, rates, and house rules — and never invents a price. Human confirmation on upgrades and exceptions.
Stack · Cerebros · agentic concierge · on-premise CRM
Documents, berths, and inland transfer stop living in three inboxes. The site calculates from your rules; the agent proposes; a named operator releases the truck.
Stack · sovereign inference · edge twin · HITL release
Research in France. Delivery in the United Kingdom, the United States, China, and Africa. On-premise when data cannot leave the country.
Talk with a systems architect. We review the stack you already have and name where agents create measurable work — not a slide about “AI transformation”.
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