AI Service Assistant for a Growing SaaS Platform
The situation
Customer-support teams needed faster access to scattered product information spread across documentation, release notes, and internal guides.
What needed to change
Customer-support teams needed faster access to scattered product information spread across documentation, release notes, and internal guides.
What we learned first
We mapped where support knowledge lived, how agents searched for it today, and which content was safe to surface. We identified clear guardrails: only approved sources, transparent citations, and human escalation for anything uncertain.
What we built
A retrieval-based AI assistant connected to approved knowledge sources, with human escalation and usage monitoring.
How it fits together
Content from approved sources is indexed into a retrieval layer. Agent queries are answered by grounding a language model in the retrieved passages, with citations returned alongside every answer. Usage is logged for monitoring and continuous improvement.
How we delivered
We delivered a focused first version quickly, then iterated based on real agent feedback — refining retrieval quality, escalation flows, and the interface until it fit naturally into the support workflow.
Faster knowledge access, improved response consistency, and reduced repetitive search work for support agents.
Illustrative case study. Details are representative and do not reference a named client.
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