Custom AI chatbot with retrieval-augmented generation
Edifycode built a support assistant that combined a controlled prompt layer with document retrieval, response tracing, and escalation paths for unanswered or low-confidence requests.
Client need
The support team needed faster, more consistent answers across product docs, onboarding guides, and policy content.
Solution
A chatbot with indexed knowledge sources, source-aware response generation, and fallback routing to human support.
Outcome
Lower first-response time, cleaner support triage, and higher answer consistency for repetitive support questions.
What Edifycode delivered
We structured the knowledge base, designed retrieval logic, created grounding and escalation rules, and shipped an application layer that made the assistant usable for both customers and internal support staff. The system was built to expose sources, track low-confidence answers, and support iterative tuning after launch.
This work aligned closely with our AI software development service and informed later investments in vector search and automation workflows.
Related internal links
Vector database for document search
Related retrieval infrastructure work.
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