Fastino Labs, an applied AI research lab and creator of the GLiNER model family, today announced two specialized open-weight models for finance and healthcare, post-trained on NVIDIA Nemotron 3.5 Lightning. The models, Fastino-Nemotron-3.5-Lightning-Finance and Fastino-Nemotron-3.5-Lightning-Healthcare, are available on Hugging Face today under the Apache 2.0 license. Neither model was post-trained by a person; both were post-trained end-to-end by the Fastino Fine-Tuning Agent, a fully autonomous autoresearch agent also released today in private preview. The agent produced each model in less than ten hours. The finance model lifts FinQA accuracy of the base model from 15.86% to 59.23%, with gains across five financial reasoning benchmarks, while the healthcare model delivers verified gains on MEDEC and MedCalc-Bench and lifts performance on a total of eight medical benchmarks. Both models showed gains that transferred to related tasks they were never trained for. The release notes that open models specialized for finance and healthcare remain scarce, with the public FinQA leaderboard tracking three models, all proprietary, and HealthBench's leaderboard dominated by closed models. Data privacy and governance have been holding LLM adoption back for high ROI use cases, and an open weight model that a team can fine-tune and run on its own infrastructure provides domain accuracy without giving up control of proprietary data.