Atlas Copilot
An intelligent AI Agent (Atlas Copilot) that indexes internal corporate documentation, maps user operational queries using RAG (Retrieval-Augmented Generation), and acts as a 24/7 automated advisor.
Atlas Copilot was built to streamline operational inquiries for large-scale enterprise workflows. By reading manuals, standard operating procedures, and compliance documents, the agent resolves customer and staff queries instantly, freeing up human resources.
- Client
- Atlas Operations
- Industry
- AI Agent System
- Year
- 2024
- Scope
- Next.js, LangChain, RAG, OpenAI API
From problem to product.
- 01Parsing heavy, unformatted PDF and Docx files containing tabular data
- 02Avoiding model hallucinations on strict regulatory and compliance text
- 03Providing immediate, sub-3-second responses under heavy user traffic
- 04Structuring clear citations to reference document pages and paragraphs
- Custom LangChain processing pipeline with recursive text splitting
- Hybrid dense-sparse vector embedding using Pinecone DB for relevant retrieval
- LLM guardrails and prompt templates that decline answering when confidence is low
- Interactive chat interface citing document source page numbers directly
The outcomes that mattered.
Built around what matters.
Retrieval-Augmented Generation
Retrieves document facts dynamically, grounding LLM answers for extreme accuracy.
Semantic Citations
Displays clickable links directly linking users back to the source PDFs.
Real-Time Evaluator
Automated logging system tracking user helpfulness scores to optimize chunk parameters.
Multi-Format Support
Direct support for importing docx, pdf, txt, and spreadsheet operating files.
Inside the product.
Chat Dashboard
Atlas Copilot transformed our support operations. It resolved half our ticket load in the first month, and the citations build massive trust.
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