Reported impact
Business outcome
The partnership accelerated HTX's development of locally controlled AI, enhanced productivity for public-safety officers, delivered top-tier benchmark performance for Phoenix models on HTX infrastructure, and created a reusable platform that is already extending into robotics, video analytics, fire safety, and cybersecurity.
- Productivity Improvement
- Risk Reduction
- Scalability
Solution
HTX partnered with Mistral to build a sovereign public-safety AI stack instead of buying a hosted AI service. Mistral supplied the training and operational tooling-AI Forge for proprietary-data model training and AI Studio for operationalizing models-while HTX combined that with its NGINE infrastructure, product teams, and in-house engineers. The result is a locally controlled ecosystem that trains and deploys Phoenix family models, including the 123B-parameter Phoenix-VL 1.5 Medium, on HTX-owned infrastructure for Singapore-specific public-safety use cases. Proprietary data and evaluation frameworks stay inside an air-gapped environment with no web search, so domain knowledge has to be embedded into model weights before deployment. Those models are then used for mission workflows such as summarizing incident intelligence, classifying documents, providing chatbot assistance, and supporting cybersecurity response, creating a repeatable pipeline from frontier R&D to operational products.
Data flow
HTX trains Singapore-context models on proprietary data in AI Forge, operationalizes them through AI Studio, deploys them on NGINE, and then uses those models to ingest incident reports, social media, sensor feeds, and documents for decision support, chatbot assistance, and workflow automation.