Launching today
Cyris
Turns every AI decision into audit-ready evidence
20 followers
Turns every AI decision into audit-ready evidence
20 followers
Your AI agents make thousands of decisions a day. Can you prove what they did? Cyris auto-instruments 12+ LLM providers (OpenAI, Anthropic, Bedrock, Gemini, Ollama, more) with zero code changes. Every decision is logged into a tamper-proof, hash-chained audit trail. When a hospital sends a 200-question security questionnaire, Cyris auto-fills the answers from your real agent data in 90 seconds. Two lines of code. Agents discovered in 10 seconds. Your next compliance review writes itself.
Cyris
Cyris
Hello! I'm David, a current Columbia CS student. I'm super excited to be building Cyris with my co-founders!
My background is a bit different from Krish's. I've been embedded on the technical side of biotech startups and incubators, which means I've seen firsthand how AI agents get built fast and audited slowly. The compliance gap isn't hypothetical; it shows up the moment a hospital's IT team asks for a system trace and the engineering team has to piece something together from scattered logs.
That frustration is a big reason I'm building Cyris. The hash-chained audit trail is something I wish every team I worked with had from day one. Happy to go deep on the technical architecture if anyone's curious!
Cyris
Hi all, I'm Mingchuan, first-year CS+Math student at Stanford. I have a lot of background in academic research, having worked for 2.5 years at the Utah Neurorobotics Lab, to build better prosthesis control systems. I'm currently working at the NLP group at the Stanford AI Lab, doing RL research for advanced mathematical reasoning.
Through my experiences, I've realized how difficult it is to build and manage agentic workflows. Researchers often have to repeat tedious data collection processes that could be automated with these workflows, but building and maintaining them is complicated. Excited to change how teams orchestrate and trust autonomous workflows with Cyris