Presenting: Pristino Labs – Trustworthy AI for Enterprise Data
Details
Pristino Labs (http://www.pristinolabs.com) — Founder George Bezerra presenting — is building infrastructure that makes AI agents reliable enough to operate on enterprise data without constant human supervision.
Today, AI agents struggle to work safely with real business data because systems are fragmented and meaning is inconsistent across tools. This creates a “trust gap” that forces companies to keep humans in the loop, slowing down automation. Pristino Labs solves this by creating a Unified Logic Layer that encodes business intent and gives AI agents a consistent way to understand data. Their product is a standardized MCP (Model Context Protocol) server that acts like an operating system for AI agents. This allows many specialized agents to work together reliably, unlocking truly autonomous workflows across the enterprise.
Our target market is enterprise software teams and data-driven companies in the U.S. who need reliable AI automation across complex data systems and are willing to pay for infrastructure that enables safe, scalable autonomous workflows.
Our competition is custom internal AI tooling, workflow automation platforms, and LLM orchestration frameworks. Our competitive advantage is a deterministic logic layer that reduces AI errors, standardizes context, and enables multiple agents to operate safely across the data stack.
The total market size in 2024 is the enterprise AI and automation infrastructure market, and the total market revenue in 2024 is $50B+.
Top 3 challenges:
- Finding strong design partners and early traction
- Building a technical team capable of executing the vision
- Raising initial funding as a first-time founder
Our PitchBoulder ask: This will be my first time raising venture capital, and I’m looking for honest feedback from an investor perspective. What would you need to see to believe this can become a venture-scale company, and how can I improve my pitch, story, and traction to be ready for VC conversations?
