ONOSOO
Illustrative example — this describes the type of project we build, not a completed client engagement. Ask us for real references.
AI · Automation

Support copilot

An LLM assistant that drafts reply suggestions for a support team, grounded in the company's own docs and past tickets.

Engagement

AI feature integration, fixed scope

Timeline

6 weeks, weekly demos

Team

1 product lead, 1 backend engineer

The brief. A support team was spending most of their time re-answering variations of the same questions, buried in a knowledge base no one had time to search properly mid-ticket.

The approach. We built a retrieval layer over the company's existing help docs and closed tickets, then set up AI to draft a suggested reply — with sources cited — that an agent reviews and sends, rather than an unsupervised bot replying directly to customers.

What it included. Document ingestion and indexing, a retrieval-augmented drafting pipeline, an agent-facing review UI inside the existing helpdesk tool, and logging to flag drafts agents routinely rejected so the knowledge base itself could be improved.

PythonNode.jsLLMs / OpenAIPostgreSQLAWS