California – Refiant, an AI optimisation company, has launched Protea, its suite of long context AI models, with a 10 million token context window that ranks among the largest ever made publicly available.
The company announced the launch on 8 July from California, with the models accessible immediately via refiant.ai. Protea gives users immediate access to one million, five million and 10 million token models, with no waitlist or approval process.
Until now, AI has been constrained by how much it can process at once. The most capable models struggle with more than a few hundred thousand tokens in working memory, forcing elaborate workarounds to compensate for what the model cannot access. Protea removes those constraints, allowing entire regulatory archives, enterprise codebases and decades of clinical trial data, datasets that previously had to be broken apart and fed to models in fragments, to be processed in a single pass with full fidelity.
According to Refiant, the model is the first product of its kind to ship to production at this scale, delivering on what competitors have so far only promised. Users can start building on models ranging from one to 10 million tokens for free.
At 10 million tokens, Protea can hold approximately 7.5 million words in context or 15,000 pages back to back, enough to hold and understand up to five years worth of email or Slack messages, or 20 to 30 years worth of documents or reports for a single person.
The company said this opens the door to previously impossible enterprise use cases. Engineering teams could ingest an entire codebase and compress a month of analysis into a single day, insurance firms could process years of claims data in one pass, and teams building agentic workflows could enable agents to operate across vast context without losing track of earlier reasoning.
Refiant said Protea tackles the “lost in the middle” problem, a documented limitation of million plus token windows where models stay accurate at the start and end of the context but lose the thread on everything buried between.
The company was founded by Dr Viroshan Naicker, Siddharth Gutta and Mathew Haswell, a team spanning quantum mathematics, traditional finance and commercial scaling, with a conviction that modern LLMs are fundamentally inefficient and that better approaches already exist in nature. Its methods draw on evolutionary search and swarm style optimisation, mimicking how natural systems find efficient solutions to complex problems.
Refiant first applied these techniques to model compression, shrinking OpenAI’s GPT-OSS-120B to run on a MacBook Pro with 18GB of RAM. Those results helped secure a $5 million seed round led by VoLo Earth Ventures, as well as research partnerships with Imperial College London and UCL’s Sargent Centre for Process Systems Engineering.
“Long-context AI has been talked about for over a year now, but hasn’t really been commercially available,” said Viroshan Naicker, CEO and co-founder of Refiant.
Chief Product Officer and Chief Operating Officer and co-founder Mathew Haswell said customers do not need more waitlists. “Customers don’t need more waitlists. They need models they can test, break and build with. Protea is live, and we want people to use it from day one,” he said.
The Protea series is open and live, and Refiant is inviting teams to stress test the context window across different industries and use cases. Internally, the company has already demonstrated a working prototype with a 100 million context window and is exploring how best to benchmark and productionise it at that scale in future.
The launch marks the first phase of a three stage roadmap, with further announcements expected over the next three months.
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