Harvey Introduces Tenet Legal AI Model Built on Kimi K3

August 24, 2026
Harvey has introduced Tenet, its first proprietary AI model for legal work, built on Moonshot AI's Kimi K3 and further trained with Fireworks AI.

Harvey has introduced Tenet, its first proprietary AI model for legal work. Tenet is based on Kimi K3, an open weight model from Chinese startup Moonshot AI, and was further trained with Fireworks AI for long horizon legal tasks.

The model is intended to give Harvey another option alongside systems from outside providers such as OpenAI, Anthropic, and Google. OpenAI is also an investor in Harvey.

Harvey created training material by hiring lawyers on staff and through firms including Mercor and Snorkel. The lawyers created mock disputes and case files, then evaluated how models reasoned through them. The company also used synthetic data in the training process.

Tenet is not yet live in Harvey's product, and the company has not given a release date. The model is part of a broader Harvey II rollout that also includes a Memory feature for saving user preferences across tasks.

We hope you enjoyed this article.

Consider subscribing to one of our newsletters like Legal AI Weekly or Daily AI Brief.

Also, consider following us on social media:

Legal AI AI Brief AI Brief (X)

More from: Legal AI

08/20
Music IP Holdings Opens Patent Licensing for AI Music Creation
08/19
Harvey Adds DeepL Translation for Legal Documents
08/19
ARCOS Labs Launches AI Content Rights Tools
08/18
Stigg Acquires Received.ai for Usage Billing and Contract Management
08/18
NLPatent Rebrands as Clerq and Launches AI Patent Workflows

Subscribe to Legal AI Weekly

The source for the Legal AI software news, analysis, emerging applications: contract review, e-discovery, research.

AI Token Webinar

Whitepaper

AI and the Law: Discussion Paper

This discussion paper explores the intersection of artificial intelligence and legal frameworks, addressing potential legal challenges posed by AI's autonomy, adaptiveness, and opacity. It examines issues such as liability gaps, causation, and the potential for granting AI systems legal personality, aiming to foster further discussion on AI's impact on law reform.

Read more

You May Also Like