Pokee AI Releases Pokee-Isaac 28B: A 10M-Token Context Agentic Model Built to Run Inside the Customer Boundary
Long-horizon agents accumulate context faster than they resolve tasks. Every tool output, observation, and intermediate reasoning step stays in the window, and the two capabilities that matter — holding that context and staying coherent across it — have so far been available almost exclusively from cloud endpoints. That excludes regulated industries, public-sector institutions, and on-device applications, where the data is not permitted to leave the boundary at all. Pokee AI released Pokee-Isaa
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Pokee AI released a large language model designed to process extremely long documents while running on a customer's own computers rather than cloud servers. The model can maintain coherence across a 10-million-token context window, which matters for regulated industries like healthcare, finance, and defense where data cannot leave a company's network boundary. The model performs competitively with cloud-based alternatives on benchmarks measuring both general reasoning and agentic task completion, while requiring only a single GPU to run. Deployment is licensed rather than open-source, with pricing and support for on-premises, virtual private cloud, and on-device installation.
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