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An autonomous customer support AI agent trained on complex company record systems using Retrieval-Augmented Generation (RAG).
ChatQA connects to custom company files, databases, and policies, providing customers instant, precise answers to highly technical questions.
Minimizing AI hallucinations when querying outdated user manuals, and optimizing database search speed over hundreds of thousands of document pages.
We built a python ingestion pipeline that chunks data, generates OpenAI vector embeddings, and stores them in Pinecone with custom semantic filters.
Vector Index Engineering • Chunking Algorithm Tuning • LangChain Agent Configuration • QA UI Setup • Testing Hallucination Bounds
RAG Semantic Search Pipeline
Dynamic Admin Document Ingester
Instant Chat Interface Widget
AI Hallucination Guardrails
Agent Accuracy Feedback Panel
Automated 70% of support tickets for beta clients, maintaining a factual accuracy rating of 99.2% in user feedback surveys.
Interactive high-resolution media captures of the project modules. Click any layout below to open the media inspector.
