The Rootly AI Labs is a fellow-led community designed to redefine reliability engineering. We develop innovative prototypes, create open-source tools, and produce research that's shared to advance the standards of operational excellence.
- Event Or Outage: Help SREs understand if a drop in traffic is due to an external event (holiday, election, sport event...) instead of an outage
- Incident Diagram: generates a diagram highlighting what happened during an incident by ingesting the retrospective and associated codebase. LLM-powered.
- DeepSeek log analysis benchmark: distilled DeepSeek R1 and benchmarked it against other models on system log analysis.
- Reliability Engineer AI benchmark: developing an industry-standard benchmark to evaluate LLMs on system operations and incident management tasks.
- Jeba Emmanuel – Ex Linkedin Staff Engineer
- Casey Brown – Head of Platform Engineering at Venmo
- Heinrich Hartmann - Principal SRE at Zalando
- Laurence Liang - McGill Engineering
- Sylvain Kalache - Head of the Rootly AI Labs
The complexities of modern technology demand a paradigm shift in how we fundamentally approach reliability.
We began in 2021 by building a category-defining on-call and incident response platform, trusted by thousands, including Replit, NVIDIA, LinkedIn, and Figma.
Now, GenAI is simultaneously introducing new complexities and unlocking opportunities to redefine reliability forever.
To stay at the forefront of this transformation, we're launching Rootly AI Labs—a dedicated initiative exploring uncharted territories such as cognitive fault prediction, quantum-inspired optimization, self-evolving autonomic digital infrastructure, and advanced digital twin simulations.
Rootly AI Labs will operate as an open-source incubator, fostering collaboration, experimentation, and rapid prototyping. We're committed to ensuring our research benefits the entire community.
We're always eager to welcome new partners and fellows because we believe that together, we can go further, move faster, and push the boundaries of AI-driven reliability and operational excellence.