Participated · Equity · May 2026

Blitzy builds an autonomous software development platform that reverse-engineers enterprise environments, constructs a persistent knowledge graph of codebases, and orchestrates thousands of agents in parallel to execute multi-week to multi-month development projects. The platform integrates state-of-the-art models from providers including Google, Anthropic, and OpenAI, running these models 100,000+ times on each run, and achieved a record 66.5% score on SWE-Bench Pro. Blitzy reports adoption across dozens of Global 2000 customers and says its platform can drive up to 5x engineering velocity for some large enterprises. The company has more than doubled headcount in the past six months and plans to expand its research team, scale go-to-market operations, and broaden partnerships—particularly in regulated sectors like government, financial services, and insurance. Financially, Blitzy raised $200 million in a growth round at a $1.4 billion valuation to fund these initiatives.

Participated · Series A · Mar 2026

Rivia has built a unified data engine that integrates thousands of heterogeneous clinical trial data files in real time and applies trial-specific scientific logic via a proprietary library of reusable configurations. Its platform harmonizes data into operational review workflows and is launching embedded AI agents—starting with Spark, which converts natural language into publication-grade clinical visualizations—with additional agents for proactive data quality monitoring and oversight. The company says its ontology library compounds with each trial, improving performance over time, and that customers have run global trials on the platform producing measurable operational benefits. Rivia positions its stack as an interoperability layer above incumbent systems like Veeva and Medidata, aimed at reducing manual stitching of sources and accelerating decision-making. Near-term plans include scaling the team across Zurich and Boston and deploying next-generation agents to support adaptive and decentralized trial workflows, with the stated ambition of substantially lowering trial costs and speeding insights.