When you’re building production AI systems and the pipes keep leaking, it’s not your LLM’s fault, it’s the infrastructure you laid it on. The whole stack is buckling under the weight of yesterday’s paradigms, retrofitted Spark jobs, and duct-taped pipelines no one wants to own. That’s the problem Typedef was built to solve, by skipping the legacy trauma and going straight to the source.
Typedef just stepped out of stealth with a $5.5M seed round, led by Pear VC with Verissimo Ventures, Monochrome Ventures, Tokyo Black, and angels like Wes McKinney and Chris Riccomini backing the vision. And the vision is loud and clear: a fully serverless, inference-first data engine built from first principles for AI-native workloads. If you’ve ever tried scaling an LLM pipeline and felt like you were debugging a haunted cluster, you’ll understand why this matters.
This isn’t about polishing old tools, it’s about scrapping them. Yoni Michael (Co-Founder & CEO) knows the cost of duct tape better than most, he built Coolan, sold it to Salesforce, and watched what happens when infra hits scale. Kostas Pardalis (Co-Founder & CTO) has architected distributed systems at Tecton and Starburst Data, he’s the type who doesn’t just write code, he writes the foundations that keep other people’s models from falling apart. Together, they’ve turned years of pain into a system that doesn’t just run AI, it speaks its language.
Think of Typedef as Spark if it had been born in 2025 and raised on LLMs instead of batch jobs. It unifies search, inference, and transformation into one engine. No clusters, no provisioning, no Frankenstein architectures. You get deterministic pipelines layered over non-deterministic models, token management that doesn’t melt under pressure, and observability that lets your ops team sleep again.
Early adopters like Matic are already putting it to work, using Typedef to extract semantic meaning from messy insurance data, reducing E&O risk and operational errors. And the open-source Fenic framework? A PySpark-style DataFrame API tuned for LLMs, not CSVs. Typedef isn’t just showing up to the AI infrastructure party, they’re DJing the set.
This $5.5M round is fuel for the fire. Engineering and product teams are growing. Governance, observability, and multicloud are on deck. The target market? Enterprise teams who are tired of pilot paralysis and want real deployments with real uptime. Financial services, healthcare, ecommerce, and tech, if you’ve got data and ambition, Typedef has an engine ready to move it.
