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Fastcase Sues Alexi Over Unauthorized AI Training Using Licensed Case Law

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16

Why it matters

Fastcase Inc., the legal research platform owned by Clio, sued Canadian AI company Alexi Technologies Inc. in federal court in Washington, D.C. on November 26, 2025, alleging breach of a 2021 data license agreement. Fastcase claims Alexi used licensed case law to train commercial generative AI models and display full-text decisions to users—uses explicitly prohibited under the original contract's "internal research purposes" restriction. The agreement permitted Alexi's staff attorneys to prepare client memoranda using the data, not to build a public, competing legal research platform. Fastcase seeks an injunction requiring Alexi to destroy both the datasets and the AI models trained on them, treating the model weights as infringing derivative works.

A federal judge in the District of Columbia will hear arguments this week on the core dispute: whether Alexi's pivot from a human-reviewed legal memo service to an AI-driven platform violates the contract's scope. Alexi argues it disclosed its commercial AI ambitions from the start and that the agreement implicitly permitted data use for AI-generated legal support. Fastcase counters that Alexi's expansion beginning in 2023—particularly its shift to publishing Fastcase-sourced case law directly to end users—constituted a material breach. The license was terminated in October 2025 after Alexi declined to change course.

The ruling will likely establish precedent for how courts interpret "internal use" restrictions in data licenses when a licensee's product evolves. A win for Fastcase could give data licensors powerful leverage to constrain AI applications of licensed material, while an Alexi victory could force licensors to explicitly carve out AI training rights in future contracts. The stakes extend across the legal tech industry: Clio's recent $1 billion acquisition of vLex signals consolidation among data holders, and this case will determine whether companies can build commercial AI products on third-party data without explicit permission. For practitioners, the outcome will reshape how legal data licenses are drafted and enforced.

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