Enterprise AI agents that report
Most “AI agents” are a chatbot with tools glued on. Cybernecs builds task-specific enterprise AI agents with a written mandate, a named human on high-stakes actions, and an organisation graph (Cerebros) they can actually reason on.
What enterprise buyers are actually searching for
The crowded head term is “AI agents”. The commercial intent that matches Cybernecs is narrower: enterprise AI agents that can call internal systems, stop when the mandate says so, and leave a trace. That is the difference between a demo and an operating layer. We design cognitive agents, agentic surfaces, and HITL gates — not another copilot bolted to a ticket queue.
Not a chatbot in the corner
A workforce that reports needs identity. Each Cybernecs agent has a code, a memory horizon, a gate, and a never-line (silent payments, silent deletes, untraced model calls). Public cards live on /agents and as A2A JSON at /.well-known/agent.json. Operators still own financial, destructive, and security decisions.
Where the work lands
Hospitality and travel: a private agent that reads inventory and house rules and never invents a price. Maritime and freight: customs, berths, and inland transfer in one graph; a named operator releases the truck. We name the architecture. We do not invent client percentages on this page.
How a project starts
Observe the real operation, model the company graph, connect pipes with policy, then deploy agents with bounded autonomy. Automation comes after the mandate is signed. Talk with a systems architect from Paris, London, the USA, China, or Africa — or request on-premise from the first brief.