About
BUILDING THE INFRASTRUCTUREFOR TRUSTWORTHY ML DATA.
Agentiks is a defense system for the single weakest point in modern ML pipelines: the data that flows in. We started building because the stack we needed didn't exist.
Our thesis
Data integrity is the next security category.
ML has moved from research to infrastructure. Once a model ships, the data that trained it becomes the attack surface — harder to audit than code, easier to poison than code, and regulated differently than code. We think the teams that train on ingested data need the same rigor around their inputs that they already have around their outputs.
What we build
Three commitments that shape every decision.
Defense in depth
No single layer catches everything. We ship six, orchestrated together, each with its own specialty and failure mode.
Attested, end to end
Every sample, every verdict, every detector score — signed, versioned, and replayable. No unexplainable decisions.
Continuously learning
A verdict model that retrains on live signals. New attacks get encoded into the defense stack in hours.