Every project here started with a team stuck on a hard, expensive problem and ended with AI running in production. One is our own product; the rest are client work under NDA. Pick a story to see the problem, what we built, and what changed.
Agent-based contract lifecycle management
Contracts scattered across PDFs, Word files, spreadsheets, scans, and email, reviewed by hand. We built an agent-based platform that pulls every legacy and new contract into one AI repository, extracts the metadata, and reviews each contract against your playbook for compliance and risk.
Document AI, computer vision & compliance
Submission-ready files of 100-200 pages, checked by hand for index accuracy, page continuity, duplicates, blanks, and up to 200 signatures and stamps. We built a document-AI pipeline that verifies the whole file in one automated pass, with a human reviewer giving the final sign-off.
Agentic AI, RAG & distributed systems
A huge consumer audience needed instant, trustworthy answers with live information, cited sources, and multiple languages. We built a production conversational-AI backend that streams answers in real time using LangChain and LangGraph agents over the Model Context Protocol, citing every source automatically.
Text-to-SQL agents & self-serve analytics
Investors, partners, and analysts sat on a rich company database they couldn’t use without waiting for someone to write SQL. We built a conversational agent that turns plain-language questions into governed SQL against the live database, tailored to each user’s role, with memory across a conversation.
Have a workflow that looks like one of these?
Bring one workflow to a free 30-minute strategy call and we’ll map the system, the deployment, and the outcome, no commitment.