Document Analysis Engine is an agent-powered knowledge workspace for uploading documents, asking natural-language questions, and receiving grounded answers with visible sources and reviewable agent steps.

Long reports, policies, research files, and technical documentation often contain the answer someone needs—but finding it can mean repeatedly searching, skimming, and cross-referencing hundreds of pages.

I built Document Analysis Engine to turn that material into an interactive knowledge workspace. Users can add PDF, text, or Markdown files, ask questions conversationally, and receive answers grounded in relevant source passages. The system can also inspect the available document collection, summarize coverage, and generate simple visualizations when those actions are more useful than another text response.

The goal is not merely faster search:

Grounded answers first: Responses begin with relevant document evidence rather than relying entirely on a model’s general knowledge.

Visible sources: Users can inspect the excerpts supporting an answer instead of accepting confident-sounding output without evidence.

More than simple retrieval: The agent can search the knowledge base, inspect available documents, calculate statistics, or generate a chart.

Transparent actions: The interface can show which steps the agent took and what those actions returned.

Conversation continuity: Follow-up questions retain their session context, allowing an investigation to develop naturally.

Adaptable delivery: The engine supports multiple document formats, replaceable language-model providers, API and command-line access, and isolated visitor workspaces in its public-demo configuration.

Document Analysis Engine can reduce the time required to explore reports, internal knowledge bases, policies, research collections, technical documentation, and client-provided source material.

It is especially useful when answers must remain reviewable. A user can move from a question to a grounded response, inspect the evidence, and continue asking follow-up questions without losing the thread of the analysis.

I designed and implemented the document-processing workflow, searchable knowledge layer, agent and tool interactions, conversation memory, source tracing, API, chat interface, command-line workflow, chart generation, session isolation, tests, deployment entry point, and technical documentation.

Document Analysis Engine turns static files into an interactive, evidence-linked workspace—helping users move from document overload to answers they can inspect and trust.