MegaDoc
Real-world problems I've architected solutions for. Each case study shows the business challenge, the architectural approach, and measurable outcomes.
MegaDoc is the reference implementation validating these patterns in production.
Legal teams spend 40+ hours per week reviewing contracts manually. AI assistants hallucinate clause interpretations, creating compliance liability. No audit trail for regulatory review.
Legal Domain Profile with zero-hallucination enforcement. Every response must cite source clause. RAG pipeline with mandatory context validation before generation.
Manual audit preparation takes weeks. Anomalies hide in thousands of documents. Regulators require complete evidence trails that manual processes can't guarantee.
Multi-modal document pipeline with structured data extraction. Pattern analysis layer for anomaly detection. Immutable audit trail with cryptographic hashing.
Clinicians need to cross-reference imaging with patient records quickly. Generic AI risks HIPAA violations. Safety-critical context requires evidence-based responses only.
Medical Domain Profile with safety-first guardrails. Vision RAG for imaging analysis. Automatic PII redaction before any model inference.
Unplanned downtime costs $100K+ per hour. Field technicians can't access manuals offline. Error codes need exact part numbers, not AI speculation.
Technical Domain Profile with specification accuracy. Vision defect detection. Offline-capable with cached embeddings for field deployment.
AI agents need structured document access but most platforms require human mediation. LangChain and Claude integrations lack standardized document tools. CI/CD pipelines can't automatically process document artifacts.
MCP/REST layer enabling AI agents to treat MegaDoc as a first-class document tool. Stateless API design for horizontal scaling.
AI Agent → Document Tool → Structured Data → Action
Knowledge scattered across Confluence, SharePoint, Git, and runbooks. New engineers take 3+ months to onboard. 80% of Slack questions are answerable from existing docs.
Unified Knowledge Graph with RAG-based search and mandatory citations. Cross-platform indexer with deduplication.
Auditors require evidence linking regulations to internal controls. Manual gap analysis takes weeks. Policy documents become stale without continuous mapping.
Policy-to-Control Mapping Engine linking GDPR, ISO, SOC 2 to internal controls. Automated evidence collection from documents and tickets.
Support agents spend 40% of time searching for answers. Similar incidents get different responses. Escalation happens too late due to missed sentiment signals.
Multi-Channel Intelligence Layer ingesting tickets, chats, and FAQs. Sentiment-aware escalation signals with similar-incident matching.
Bring Your Own Database for natural language queries. Zero SQL knowledge required, complete data sovereignty.
Business analysts query legacy databases without IT provisioning.
Prospects test AI capabilities on their own data before commitment.
Finance teams generate complex aggregations from Excel exports.