NEWRead our blog:The Most Important Eval isn't on a Leaderboard→
Power agents in production that learn from experience.
NeoSigma is the infrastructure layer for agents in production - turning production data into a living quality layer that compounds into proprietary intelligence across users, teams and organizations.
The bottleneck in building AI systems isn't writing code anymore. It's everything that comes after - building reliable intelligent systems that can sustain and improve themselves over time. We're building the future for this next generation of AI systems that learn automatically from experience.
If you are interested in our mission, we would love to hear from you to join us!
Backed by angels and leaders like Jeff Dean and others from OpenAI, Google DeepMind, World Labs, Mercor, Decagon.
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Companies that close the loop between production signals and evaluations will win.
Shyamal Anadkat
ex-OpenAI, Applied Evals
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Intelligence in an agent is as much the ability to solve problems as it is the ability to learn from experience and adapt to an ever-changing environment. Neosigma is paving the way towards making this an operational reality.
Victor Barres
Tau bench co-creator, Researcher at Sierra
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NeoSigma brings to life: turning production issues into a continuous feedback loop that improves reliability without manual overhead.
Chirag Mahapatra
Director of Engineering, Mercor
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Transforming performance in production environments requires much more than better models. It requires systems that learn from their own mistakes at scale.
Reah Miyara
Senior Director, Google · ex-OpenAI Post-Training
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NeoSigma addresses the challenge of making agents reliable by catching regressions, debugging failures, and maintaining evaluations and reliability as systems evolve and user behaviors drift.
Manoj Soundararajan
Product @Decagon
