EngramLab and Harvey open source synthetic law firm dataset with over 100 million tokens

Harvey and EngramLab have released an open-source synthetic dataset containing more than 100 million tokens, essentially building a fake law firm’s entire body of work so that real AI systems can learn how actual firms operate. The dataset covers over 250 synthetic client matters across 46 clients, with roughly 10,000 individual files representing the kind of institutional knowledge that typically lives inside the heads of partners who’ve been practicing for decades. What the dataset actually contains EngramLab’s contribution centers on its memory-layer technology, which the company claims can compress organizational context enough to cut token usage by up to 100x. In practical terms, that means an AI system could process the equivalent of a partner’s career worth of institutional knowledge without burning through compute budgets. Harvey, for its part, has been building toward this kind of release. Earlier in 2026, the company open-sourced the Legal Agent Benchmark, known as LAB, which established standardized ways to measure how well AI agents perform on legal tasks. The synthetic dataset is a natural companion piece, giving researchers and developers actual training material to w...