A small agent that owns one job — and does it well for years.
Build · 6–10 weeks · fixed priceNot a general-purpose assistant. A bounded agent built for a specific job: triage, qualification, research, follow-up. With tool-use limited to vetted APIs, every action logged, and a human always able to override.
A general-purpose AI assistant is too vague to own real work.
If the assistant owns everything, it really owns nothing. No one trusts an output without a clear scope.
Letting a model call any API on your behalf is how production incidents start. Tool-use needs to be vetted.
An agent without a clear human override is a liability. Operators need to be able to step in cleanly.
A bounded job. Vetted tools. Auditable trail.
- Scope contract
- One job, with explicit success criteria, refusal cases and escalation paths
- Tool-use
- A small, vetted set of internal APIs with strict input/output contracts
- Memory
- Per-task working memory; no quiet long-term state surprises
- Human override
- Operator console with full trace, approve / reject / take-over per step
- Evaluation
- Golden cases for the job · replays · drift alerts before users notice
- Observability
- Per-decision logs · cost per task · refusal rates · drift dashboards
An agent your operations team treats like a teammate, not a toy.
The agent owns the boring half of one job. Your team owns the judgement half. Override is one click. Audit is one query. New behaviour ships behind evals.
Best when there's already a reliable workflow underneath.
Workflow Automation
An agent without a clean workflow underneath is amplifying chaos. Workflow comes first.
/services/rag-knowledge-systemRAG Knowledge System
Agents that need to reason over your documents do so via the same retrieval layer.
/services/ai-auditAI Audit
The audit decides whether a job is bounded enough to be a good fit for an agent at all.
Pick one job. Let an agent own it.
We start with an audit to make sure the job is the right shape, then build the agent — bounded, observable, overridable.