Fire blog

Agentic AI can act unpredictably, causing data loss, compliance failures, and safety incidents.

AI evaluation is the backbone of reliable LLM and agent systems. Learn what to measure and how to measure it. How continuous evaluation connects to guardrails, observability, and prompt management.

Ranger is an open, production-ready Tool Selection Quality model. Lightweight, fast, and accurate, Ranger helps agents choose the right tool and parameters so your pipelines keep working. Download Ranger-mini on Hugging Face and plug it into your agent pipeline in minutes.

Discover top LLM evaluation frameworks, metrics, and benchmarks like G-Eval and LLM-as-a-Judge to build reliable generative AI systems.

New Webinar! What’s the missing link between AI hype and AI adoption? Reliability! Join Gilad Ivry and Adir Ben Yehuda from Autonomy AI as they share hard-earned lessons on building trustworthy LLM applications.

Add real-time evaluation, hallucination detection, and policy enforcement to your n8n flows with Qualifire. Step-by-step HTTP Request node guide, input and output guardrails, observability tips and cURL examples.

Ensure AI reliability. Learn how Qualifire’s Paladin-mini, a compact, Open-Source Grounding SLM, precisely detects unsupported claims and grounding errors.

Navigate ISO 42001 for AI systems compliance, with practical steps for AI governance and risk management, plus tools to accelerate enterprise certification.

Discover how Sentinel stops evolving prompt injection attacks in real time with under 20 ms latency, ensuring your AI delivers exactly what you envisioned.