Participated · Series B · May 2022

Traceable builds an AI-driven platform that analyzes API usage data to learn normal behavior and spot deviations, running on-premises or as a fully managed cloud service. The software discovers and catalogs existing and new APIs in real time, including undocumented and orphaned endpoints, and offers tools for API discovery, testing, protection and threat hunting. Traceable trains in-house models by fine-tuning open-source large language models with labeled attack data to detect modern threat scenarios. The company analyzes roughly 500 billion API calls per month for about 50 customers and says most clients are enterprises, with pilots being investigated for governments. Management projects revenue to double this year and describes its margin profile as healthy and improving; the company is not profitable by choice as it continues to invest responsibly. Traceable had about 180 staffers at the time of the report and expects headcount to reach 230 by year-end 2024 as it scales product, customer engineering and partnerships. Traceable AI builds API security software that uses distributed tracing and context-based behavioral analytics to learn normal application behavior and surface anomalies. Its platform catalogs shadow and orphaned APIs in real time, maps app topologies and data flows, and assigns risk scores using multiple criteria. The software runs on-premises or in the cloud and provides rich forensic data for root-cause analysis. The company has paying customers and recently open-sourced its tracing technology under the Hypertrace project to spur adoption. Leadership includes CEO Jyoti Bansal and CTO Sanjay Nagaraj; Bansal says Traceable was co-founded four years ago and is San Francisco–based. Management declined to disclose annual recurring revenue, and total capital raised to date stands at $80 million. Traceable builds a security platform that protects applications by monitoring code-level behavior. It deploys software agents that watch for anomalous actions such as unusual data movement via APIs. The product uses machine learning to learn normal behavior over time and can flag or automatically block suspicious activity. It integrates with tools like Slack to send automated warnings and can temporarily shut down API access to allow investigation. The company is positioning itself to address the shift in attack surface from networks and infrastructure to application code. Financially, Traceable announced a $20 million Series A to fund growth and product development.

Participated · Series B · Apr 2019

Harness is a San Francisco–based AI software delivery platform designed to automate and optimize post-code DevOps workflows. Its core offering combines specialized AI agents, a Software Delivery Knowledge Graph, and orchestration tools to remove manual toil from building, testing, and releasing software. By learning from organizational context, the system adapts to engineering teams’ needs and can act autonomously to speed releases and cut costs. Customers such as United Airlines and Choice Hotels report up to 75% faster release cycles, 60% reductions in cloud spend, and 10× overall DevOps efficiency. The company’s near-term plans for the fresh capital include accelerating product innovation, expanding global operations, and deepening R&D. Harness positions itself as the intelligent backbone for modern software delivery, aiming to be indispensable infrastructure for engineering organizations.