Netra product announcements, feature explainers, integrations, setup guides, and platform capability updates.
Compare Netra vs Maxim AI for AI agent observability in 2026. Explore how they differ across tracing, evaluations, simulations, prompt management, behavioral analytics, and production reliability to find the right platform for your AI systems.
Debugging AI agents usually means bouncing between your IDE, dashboards, and logs to piece together what went wrong. Netra MCP brings that observability context directly into your coding assistant, letting you query live traces and pinpoint failures without ever leaving your editor.
Tracing can explain what happened in a single AI agent run, but it cannot reveal how the system is performing over time. Explore how Netra goes beyond LangSmith-style tracing with continuous evaluation, multi-turn simulation, and tenant-aware observability for reliable production AI agents.
We build AI agents. We've shipped twenty five of them — travel, customer service, scheduling, voice transcription. Every single one broke in production des...
Last March, our travel AI sent a user to a resort that doesn't exist. They'd asked for a road trip itinerary. The AI confidently included "Sunoutd...
