Ollaya: Open-Source Ollama for Jev-Style Decision Models
llama open-source
| Source: HN | Original article
Ollaya launches as an open‑source platform that lets developers run Jev‑style decision models locally via a TypeSafe‑compatible API, mirroring Ollama’s approach for language models.
Ollaya, a new open‑source platform that mirrors the popular Ollama interface, has been launched to let developers run “decision models” on their own hardware. The project, hosted on GitHub, bundles models such as Laya, Decider, NLI and GLiClass behind a TypeSafe‑compatible API, delivering typed, calibrated answers in milliseconds. Users can submit queries as plain text or JSON and receive structured responses with probability scores in a single forward pass, all without sending data to the cloud.
The release matters because it lowers the barrier to private, high‑speed inference for tasks that require deterministic, probability‑aware outputs—ranging from ticket triage to email routing. By keeping the computation local, Ollaya addresses growing concerns over data privacy and latency while staying within the open‑source ecosystem. It also expands the practical utility of decision‑model research that has recently been benchmarked on NVIDIA GPUs, as detailed in our earlier coverage of the 421 M‑parameter Laya model [2026‑09‑25].
Looking ahead, the community will be watching how quickly model contributors expand the catalog and whether Ollaya’s performance holds up against larger proprietary alternatives. Integration with existing workflows, support for additional hardware accelerators, and real‑world case studies from enterprises will be key indicators of the platform’s impact. If adoption accelerates, Ollaya could become a cornerstone for organizations that need fast, private, and explainable AI decisions without the overhead of cloud services.
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