MegaDoc
A multi-modal document intelligence platform I built to demonstrate production AI patterns: RAG pipelines, vector embeddings, and privacy-first architecture.
Domain-Agnostic: Switch contexts (Legal/Medical/Finance/Industrial) instantly via dynamic system prompting.
A reference platform I designed and built to solve real enterprise problems: transforming static PDFs, technical manuals, and field photos into a live, queryable knowledge base—without training custom models.
Bring Your Own Database
Three ways to query your data: Document RAG, SQL Sandbox, or Direct Chat—all with Smart Routing and full observability.
Upload documents (PDF, Word, Excel) or databases (SQLite, CSV, SQL dumps). Multi-modal support converts images to searchable descriptions.
Queries are analyzed for complexity and routed to optimal models. Simple queries use fast free-tier models; complex analysis uses premium models.
Natural language to SQL for databases, RAG chat for documents, or direct chat. All with X-Ray debug panel showing latency, tokens, and model decisions.
Production-grade observability, cost optimization, and safety evaluation built-in.
Real-time request tracing with TTFT (Time To First Token), latency metrics, and token usage. Enable debug panel with ?debug=1.
Intelligent model selection based on query complexity. Routes simple queries to free-tier models, complex analysis to premium—85% cost reduction.
30 adversarial prompts across 12 attack categories (jailbreak, injection, PII extraction). Automated CI/CD integration for PR safety checks.
Built for regulated industries. We prioritize data privacy, zero-retention architecture, and complete auditability.