Side-by-side comparison of AI visibility scores, market position, and capabilities
Seattle precision ag laser weeding robot in 14 countries eliminating 10B+ weeds; $177M total ($70M Series D 2024 + $20M Series D-2 Giant Ventures) with LPM trained on 40M+ plants competing with Blue River Technology for herbicide-free precision weeding.
Carbon Robotics is a Seattle, Washington-based precision agriculture robotics company — backed with $177 million in total funding including a $70 million Series D in 2024 and a $20 million Series D-2 extension led by Giant Ventures — providing specialty crop farmers with the LaserWeeder: the world's first commercial AI-powered laser weeding robot that eliminates weeds using high-powered lasers guided by computer vision without chemical herbicides or manual labor. Operating in 14 countries across North America, Europe, and Australia, owned and operated by 100+ growers, with 10+ billion weeds eliminated since 2022, Carbon Robotics' Large Plant Model (LPM) — trained on 40+ million labeled plants from three continents — enables real-time identification and precision destruction of weeds growing between crop rows. Named to the 2024 CNBC Disruptor 50 and TIME's Top GreenTech Companies of 2024. Founded in 2018 by Paul Mikesell in Seattle.
OpsLevel is a developer portal and service catalog for tracking service ownership, maturity scorecards, and production readiness across microservices.
OpsLevel is a developer portal platform that gives engineering organizations visibility into the services they operate, who owns them, and how mature they are relative to internal engineering standards. At its core, OpsLevel maintains a service catalog that maps every microservice, repository, and infrastructure component to a team owner, populating metadata automatically from integrations with GitHub, GitLab, PagerDuty, Datadog, and cloud providers. This catalog becomes the authoritative source of truth for answering questions like who to contact about a service, what tier of reliability it requires, and what dependencies it has — questions that are often unanswerable at engineering organizations that have grown past the point where everyone knows everything.
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