Published Research
Published Research
MAY 11, 2026 • MODEL
GLiNER2-PII: A Multilingual Model for Personally Identifiable Information Extraction
GLiNER2-PII: A Multilingual Model for Personally Identifiable Information Extraction
Urchade Zaratiana, Ash Lewis, and George Hurn-Maloney
Fastino Labs builds GLiNER2-PII, a compact 0.3B-parameter model that detects personally identifiable information across 42 entity types in messy, real-world text. It achieves the highest span-level F1 on the SPY benchmark among five compared systems, including OpenAI's Privacy Filter.
Fastino Labs builds GLiNER2-PII, a compact 0.3B-parameter model that detects personally identifiable information across 42 entity types in messy, real-world text. It achieves the highest span-level F1 on the SPY benchmark among five compared systems, including OpenAI’s Privacy Filter.
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APRIL 10, 2026 • RESEARCH
Accepted to EMNLP 2026
Pioneer Agent: Continual Improvement of Small Language Models in Production
Pioneer Agent: Continual Improvement of Small Language Models in Production
Dhruv Atreja, Julia White, Nikhil Nayak, Kelton Zhang, Henrijs Princis, George Hurn-Maloney, Ash Lewis, and Urchade Zaratiana
Pioneer Agent fine-tunes small language models after deployment, automatically diagnosing production failures and retraining to fix them without degrading existing behavior. It substantially improves performance and discovers effective training techniques on its own based on feedback from inference logs.
Pioneer Agent fine-tunes small language models after deployment, automatically diagnosing production failures and retraining to fix them without degrading existing behavior. It substantially improves performance and discovers effective training techniques on its own based on feedback from inference logs.
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OCTOBER 22, 2025 • RESEARCH
Beyond Reactivity: Measuring Proactive Problem solving in LLM Agents
Beyond Reactivity: Measuring Proactive Problem solving in LLM Agents
Gil Pasternak, Dheeraj Rajagopal, Julia White, Dhruv Atreja, Matthew Thomas, George Hurn-Maloney, and Ash Lewis
Fastino Labs creates PROBE, a benchmark that measures whether LLM agents can proactively spot and resolve problems without being told to, decomposing the task into searching a personalized datastore, identifying the real bottleneck, and executing the correct fix across 1,000 realistic scenarios.
Fastino Labs creates PROBE, a benchmark that measures whether LLM agents can proactively spot and resolve problems without being told to, decomposing the task into searching a personalized datastore, identifying the real bottleneck, and executing the correct fix across 1,000 realistic scenarios.
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JULY 24, 2025 • MODEL
GLiNER2: An Efficient Multi-Task Information Extraction System with Schema-Driven Interface
GLiNER2: An Efficient Multi-Task Information Extraction System with Schema-Driven Interface
Urchade Zaratiana, Gil Pasternak, Oliver Boyd, George Hurn-Maloney, and Ash Lewis
GLiNER2 is a unified open-source 205M-parameter model that handles named entity recognition, text classification, and hierarchical structured extraction through a single schema-driven interface, matching GPT-4o's accuracy on key benchmarks while running 2.6x faster on CPU.
GLiNER2 is a unified open-source 205M-parameter model that handles named entity recognition, text classification, and hierarchical structured extraction through a single schema-driven interface, matching GPT-4o’s accuracy on key benchmarks while running 2.6x faster on CPU.
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JUNE 21, 2024 • MODEL
GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer
GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer
Urchade Zaratiana, Nadi Tomeh, Pierre Holat, and Thierry Charnois
GLiNER is a compact bidirectional transformer model that identifies any entity type in a zero-shot setting, extracting entities in parallel rather than generating tokens sequentially like LLMs. It outperforms frontier LLMs on zero-shot NER benchmarks while remaining small and fast enough for resource-constrained environments.
GLiNER is a compact bidirectional transformer model that identifies any entity type in a zero-shot setting, extracting entities in parallel rather than generating tokens sequentially like LLMs. It outperforms frontier LLMs on zero-shot NER benchmarks while remaining small and fast enough for resource-constrained environments.
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Fastino Inc. (“Fastino”) develops specialized AI models and provides APIs designed to support structured data extraction, classification, reasoning, and production AI workflows. Fastino is a technology company and does not provide legal, financial, compliance, or advisory services.
Any outputs, predictions, classifications, or decisions generated through Fastino models are based on the configuration, data, and implementation provided by the customer. Fastino does not control, verify, or guarantee the accuracy, completeness, or suitability of model outputs for any specific purpose. By using this website or Fastino’s models and services, you acknowledge that all content and outputs are provided for informational and operational purposes only and agree to our Terms of Use and Privacy Policy.
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Fastino Inc. (“Fastino”) develops specialized AI models and provides APIs designed to support structured data extraction, classification, reasoning, and production AI workflows. Fastino is a technology company and does not provide legal, financial, compliance, or advisory services.
Any outputs, predictions, classifications, or decisions generated through Fastino models are based on the configuration, data, and implementation provided by the customer. Fastino does not control, verify, or guarantee the accuracy, completeness, or suitability of model outputs for any specific purpose. By using this website or Fastino’s models and services, you acknowledge that all content and outputs are provided for informational and operational purposes only and agree to our Terms of Use and Privacy Policy.
2026 Fastino Inc.
All rights reserved
Subscribe to our newsletter
Get the latest updates on model releases, product news, and research.
Fastino Inc. (“Fastino”) develops specialized AI models and provides APIs designed to support structured data extraction, classification, reasoning, and production AI workflows. Fastino is a technology company and does not provide legal, financial, compliance, or advisory services.
Any outputs, predictions, classifications, or decisions generated through Fastino models are based on the configuration, data, and implementation provided by the customer. Fastino does not control, verify, or guarantee the accuracy, completeness, or suitability of model outputs for any specific purpose. By using this website or Fastino’s models and services, you acknowledge that all content and outputs are provided for informational and operational purposes only and agree to our Terms of Use and Privacy Policy.
2026 Fastino Inc.
All rights reserved


