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03 / AI / Software
AI Inquiry & Support Chatbot
Support information was spread across product documentation, PDFs, release notes and internal help content. We built a grounded AI assistant that retrieves relevant information before responding and escalates uncertain conversations.
68%of routine inquiries resolved without agent action
8.4 secmedian first response time
37%drop in repeat support tickets
What we built
A system designed around the actual work.
- Knowledge ingestion from PDFs and web content
- Chunking and embedding pipeline
- Retrieval with source grounding
- Website and application chat widget
- Confidence‑based escalation
- Conversation analytics
How it works
From input to action through one connected flow.
01
INGEST
Prepare approved knowledge sources
02
RETRIEVE
Search the most relevant content
03
ANSWER
Generate a grounded response
04
ESCALATE
Hand off uncertain cases with conversation context
Delivery scopeSolution architecture, workflow design, AI integration, application engineering and production implementation.
TechnologyVector database · Embeddings · LLM API · n8n · Embedded widget
Measured outcome
Operational work became visible, measurable and easier to scale.
Routine questions moved from an email queue to an immediate self‑service channel, while agents received the smaller set of conversations that actually required judgment.