Typedef

Typedef gives analytics and BI teams reconciled metrics, traceable agent answers, and the right data, fast, across every system in the stack.

Typedef integrates with warehouses, transformation tools, BI platforms, and other systems in a data stack.

Engineering posts from the Typedef team on data infrastructure for AI agents, semantic layers, and agentic analytics.

Convert PDFs into an agent-ready catalog: split Markdown into sections, build a topics index, and publish 3 minimal MCP tools for search.

Cortex Sense vs Genie Ontology: two governed context layers that pick the right definition for AI agents, but neither checks if the answer is correct.

AI coding agents don't transfer to data. Anthropic's analytics infrastructure shows why data needs governed context, not just warehouse access.

The page describes a live context layer, built from code, that validates AI responses and changes before deployment.

Factory acquires Typedef, a startup specializing in mapping dependencies across enterprise data systems. The move integrates Typedef’s technology into Factory’s coding agents, providing them with contextual data insights. Co-founders Yoni Michael and Kostas Pardalis, along with their team, are joining Factory as part of the acquisition.

Nov 2026dealroom.coNews article

Factory acquires Typedef, combining expertise in AI infrastructure and developer tools. The move consolidates resources for advancing AI systems development. Both teams will continue their work under Factory’s leadership.

Oct 2026typedef.aiNews article

Factory acquires Typedef to integrate its data context capabilities into its software development platform. The move aims to enhance developer workflows by embedding contextual data insights directly within coding environments. Typedef specializes in providing structured data interpretations for software tools, addressing a key gap in modern development workflows.

Oct 2026FactoryNews article

Typedef introduces an inference-first data infrastructure designed to address the challenges of AI pilot projects, which often fail to scale. The company secures $5.5 million in seed funding to develop production-ready workloads, aiming to reduce infrastructure management burdens for data and AI teams. This shift allows teams to prioritize innovation and competitive advantage over operational hurdles.

Jun 2025PR NewswireNews article