AI Business Assistant

A concept build demonstrating how a business can deploy an internal AI assistant grounded in its own documents and processes. The assistant answers questions with citations, searches internal knowledge, and can trigger simple workflow actions through a human-in-the-loop flow.

Teams waste hours searching across scattered documents and repeating the same answers.

A retrieval-augmented assistant grounded in the organization's own knowledge, with safe, approval-gated actions.

• Conversational interface
• Knowledge retrieval with citations
• Document search
• Workflow integration (human-in-the-loop)

Next.js frontend, Python service layer, a vector database for retrieval, and an LLM for generation, with an approval step before any action is executed.

• Retrieval-Augmented Generation (RAG)
• Semantic search over documents
• Grounded, cited responses
• Tool-calling with human approval

Designed to reduce time spent searching for information and answering repetitive questions.

Each value is labeled by how it was verified. This is a concept build; metrics shown are targets or estimates, not measured client results.