We're trying to apply the insights of category theory, dependent type theory, and functional programming to deep learning. How do we best equip neural nets with strong inductive biases from these fields to help them reason in a structured way?

We turn messy product catalogs into structured gold using LLMs. Millions of SKUs, 50+ marketplaces, real AI problems. Small team (4 people), building the backbone of AI commerce.

Sync Bio provides human cell culturing and screening as a CRO service. Our automated labs use custom hardware to acquire massive datasets involving millions or billions of cells. We perform fluorescence imaging and single-cell RNA sequencing to collect data for the next generation of computational models, including virtual cell models.

Synca uses AI to determine who in an organization needs to know what, and allows them to take immediate action. With the flood of information in today's age, people don't know what they need to know. We fill this gap and empower everyone to be experts in their domain.

We are an all-in-one modern data integration, management, workflow and analytics platform.

Syncopate builds tools to help automate financial diligence and management of long-tail financial assets. They have found product market fit with ETL/analysis tools for niche financial data, starting with music rights, and are looking to build out capabilities across more Excel + PDF-based workflows.

Syntasso is a startup empowering platform engineering teams to thrive. Their flagship open-source project, Kratix, helps companies build and manage internal platforms without reinventing the wheel.

We're building a generative-AI powered, enterprise-grade video creation platform and we've found strong product market fit. We're at Series C, have a long runway, and are seeing hockey stick growth.

We're constructing cool generative content forms.

We're an early-stage startup looking for someone passionate about detection engineering and generative AI.