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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.

AI / SoftwareVector database · Embeddings · LLM API · n8n · Embedded widget
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.