Agnost monitors production AI agents, finds silent failures, and turns trace data into tested fixes and specialized models.
Founders · Pricing · Product · How it works
- Founded
- 2025
- Team
- 2 people
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Agnost monitors production AI agents, finds silent failures, and turns trace data into tested fixes and specialized models.
Founders · Pricing · Product · How it works
Attribute AI spend to the customer, feature, team, or pull request that caused it, across OpenAI, Anthropic, Cursor, and every other provider you use. Free to start.
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Expanse predicts exactly what every job needs before it runs, so your cluster does more real work with the GPUs you already have.
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Kashikoi is an all in one simulation platform that allows you to build, evaluate and truly test your AI agent so you can fix bugs before your customers ever see them.
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Roark simulates your voice agent against hundreds of scenarios before launch, then scores every production call on 500+ audio-native metrics. Catch what breaks, prove the fix, ship with evidence.
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Trace, evaluate, and improve AI agents with one open platform. Use production data to understand behavior, collaborate on fixes, and ship better quality at lower cost and latency.
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The AI Leaderboard — independent rankings of GPT, Claude, Gemini, Llama, DeepSeek and 300+ AI models by intelligence, speed and price. Composite LLM Stats Score updated continuously from public benchmarks and live API metrics.
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Voker is the Agent Analytics Platform for monitoring and improving your AI agents. Companies like Dutch.com use our SDK to build better agents. Alex and Tyler met at a high-growth E-Commerce startup where Tyler was running Technology…
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Routing and monitoring for reliable AI apps - the LLMOps platform behind the fastest-growing AI companies.
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ARC Prize Foundation is a nonprofit advancing open-source AGI research through benchmarks & prizes.
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ML models are only as good as the datasets they're trained on, and that means that most improvement to model performance comes from improvement to the quality and diversity of their datasets. Our tooling makes it easy for ML teams to…
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Turn production failures into your next improvement. Find agent issues, build regression tests, and compare changes before your next release.
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Historically, quantitative models are domain specific. Brilliant people spend their best years testing features, tuning hyperparameters, and iterating architectures within a narrow domain. But scale is the panacea: large models will…
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Trace every run. Auto-fix silent failures. Simulate before shipping. Raindrop helps you detect agent issues and prevent them from happening.
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Turn production conversations into patterns your team can act on. Investigate from your IDE and measure changes in cost, quality, and usage.
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Prompt engineers, visual artists and AI data scientists are using Magicflow to run experiments at scale and perfect their pipelines Our product is ready to use: https://console.magicflow.ai try it out! we have some preloaded examples…
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Find and fix your agent’s most critical failures in hours, not days. Atla helps developers cut time spent on manually reviewing traces. Atla’s LLM judge evaluates your agent step-by-step, uncovers error patterns across runs, and…
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