AI Agents and Operational Copilots
We design agents and copilots for triage, support, analysis, documents and assisted execution with tools, limits and supervision defined.
Agents that know what they can do, when to request approval and how to log each relevant action.
Before implementation
- owner
- responsible for the process and the decision
- criterion
- metric, error cost and automation boundary
- evidence
- available data, gaps and review trail
How we work
The service becomes a sequence of small, reviewable and documented decisions.
- step 1
- Role, tool and boundary design
- step 2
- Controlled memory, context and knowledge base
- step 3
- Human approval for critical actions
Use cases
- Internal and external support
- Request and document triage
- Copilots for operations, support and product teams
Deliverables
- Agent and tool spec
- Prototype in a controlled environment
- Evaluation criteria, logs and escalation
When we do not follow this path
We do not sell agents as shortcuts. Without a clear process, an agent only accelerates confusion.
Questions before scope
Short answers to understand when this path deserves to become a project.
Can agents execute actions without supervision?
Only when risk is low and limits are defined. In sensitive actions, the agent prepares, explains and escalates for human approval.
How do you evaluate whether an agent is ready for use?
We evaluate role, tools, knowledge base, response criteria, logs, escalation, error rate, source coverage and situations where it must stop.
Who is accountable if the agent fails in production?
A human owner is defined before go-live, and the agent logs every action so what happened can be reconstructed. On sensitive actions it stops and escalates; a failure never becomes a black box.