Autonomy is earned, not switched on.
We start narrow, prove the agent against real conversations, and widen its scope only on evidence. Your team watches from the console the whole time.
Four phases, one conversation type at a time.
Timelines depend on your knowledge base and systems; we agree them after the audit rather than guess here.
Knowledge audit
We read what your agent would read: help centre, policies, macros, past tickets. We find the gaps, the contradictions and the questions with no written answer.
A knowledge map and a shortlist: which conversation types an agent can answer today, which need better docs first, which should always go to a person.
Scoped pilot
One conversation type, live, with guardrails at their strictest. The agent drafts; your team reviews from the console; nothing sends without approval at first.
Evidence: groundedness rate, escalation accuracy, and a list of every wrong answer — with the fix for each.
Adversarial evaluation
We try to break it: ambiguous questions, prompt injection, out-of-scope requests, angry customers, missing data. The failure modes get fixed before customers find them.
A signed-off scope: what the agent may send unsupervised, what still needs review, what it must never do.
Earned autonomy
Scope widens conversation type by conversation type, each on the evidence of the last. Review sampling continues even at steady state.
A system your team runs: console, playbooks, documentation — and us on call when your products or policies change.
How we know it’s working.
Not vibes, and not a single “deflection rate”. We agree three measures before launch and review them on a fixed cadence with your team:
- Groundedness — sampled answers traced to their sources. A wrong citation counts as a failure, even if the answer read well.
- Escalation quality — did it hand over when it should, with context the reviewer could act on? Both directions count: missed escalations and needless ones.
- Customer outcome — was the question actually resolved? Measured per conversation type, not blended into a vanity average.
Phase one is reading, not building.
Send us your help centre and your hardest question type. The audit will tell us both whether this is worth doing.
Email info@finlogiq-ai.comNorwest, NSW 2153, Australia