Sentient

• Sentient is building open-source artificial general intelligence infrastructure with community ownership of models.

• Its fingerprinting technique embeds ownership signals into open models so contributors retain a claim after release.

• SENT is the network token.

• Supply allocated across community, ecosystem and investors.

• Used to reward model contributions and govern the protocol.

Pros:

• Model fingerprinting is a novel approach to the open-versus-monetised tension in AI.

• Raised one of the largest seed rounds in the decentralised AI category.

• Has released working models rather than only research.

Cons:

• Open-weight models can be fine-tuned to remove ownership signals, which is an active research contest.

• Competes against very well-funded open model releases that are simply free.

• Revenue model depends on enforcement mechanisms that are not yet proven.

• Exposure to open-model AI with a mechanism for contributor compensation.

• Substantial funding and a research team with published output.

• Weigh whether fingerprinting survives adversarial fine-tuning.

• Ownership signals embedded in open model weights, letting a model be freely distributed while its creators retain an enforceable claim.

• Open models cannot be monetised and closed models cannot be community-owned.

• Fingerprinting attempts to make a model both open and attributable, which is the tension the category has not resolved.

• Founded by Himanshu Tyagi, Pramod Viswanath and Sandeep Nailwal, who also co-founded Polygon.

• Backed by Founders Fund, Pantera Capital and Framework Ventures.

• No public ICO. Distributed through ecosystem and community allocations.

• Fingerprint removal through fine-tuning is an unresolved adversarial problem.

• Free open models from large labs compete directly.

• Enforcement of ownership claims across jurisdictions is untested.

• Very early stage relative to the funding raised.