AI Agent Systems

Autonomous and semi-autonomous agents that do real work inside real operations — researching, drafting and monitoring — rather than agents that demo well and fail in production.

Most agent demos collapse on contact with reality: unbounded permissions, no configurability, and workflows that don’t match how an actual operation runs. In production, an agent with the wrong access or the wrong assumptions is a risk, not a feature.

We studied where agents break in production — permissions, reliability, and the gap between a generic workflow and a specific operation’s real one.

Agents with permissioned access and workflows configured to each operation, with a human in the loop where judgment belongs — autonomy scoped deliberately, not maximised.

Systems that research, draft and monitor, built around each operation’s actual process and access boundaries.

The test is production: whether the agent keeps doing useful, correct work inside a live workflow. [CONTENT REQUIRED: specifics]

[CONTENT REQUIRED: impact metrics]

• Agentic AI
• Permissioned access controls
• Workflow configuration
• [CONTENT REQUIRED: precise stack]