Agnost AI vs EvalsHub: Which is Better in 2026?
A comprehensive comparison of Agnost AI and EvalsHub covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose Agnost AI if:
- →You need continuous analysis of production conversations for stuck, frustrated, and non-converting users or failure patterns ranked by impact instead of raw anomaly lists
Choose EvalsHub if:
- →You want more affordable paid plans (from $39/mo)
- →You need natural-language rubrics with weights and thresholds or llm-as-a-judge scoring tailored to specific use cases
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Agnost AI vs EvalsHub: At a Glance
Pricing Comparison: Agnost AI vs EvalsHub
Understanding the pricing differences between Agnost AI and EvalsHub is crucial for making the right choice. Here's how their plans compare side by side.
Agnost AI Pricing
EvalsHub Pricing
💡 Pricing takeaway: Both Agnost AI and EvalsHub offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from Agnost AI and EvalsHub stacks up.
What Makes Each Tool Unique
🔵 Unique to Agnost AI
Features available in Agnost AI but not in EvalsHub:
- ✓Continuous analysis of production conversations for stuck, frustrated, and non-converting users
- ✓Failure patterns ranked by impact instead of raw anomaly lists
- ✓Reviewed fixes and autonomous pull requests generated from production signal
- ✓Feature-request mining from conversations users already had
- ✓Conversion-pattern analysis for sales and support agents
- ✓Error-rate and analytics tracking across agent deployments
🟣 Unique to EvalsHub
Features available in EvalsHub but not in Agnost AI:
- ✓Natural-language rubrics with weights and thresholds
- ✓LLM-as-a-judge scoring tailored to specific use cases
- ✓Automatic regression detection and cross-model comparison
- ✓Red-team suite for prompt injection, jailbreaks and PII leakage
- ✓CI/CD integration and online auto-evals
- ✓AI-generated dataset rows and trace-span based experiments
Use Case Recommendations
Best for: Agnost AI
Agnost AI is product analytics for teams building conversational agents, built around a specific gap: your evals pass and production still fails. It continuously analyzes real production conversations to find where users get stuck, get frustrated, or fail to convert, clusters those into patterns, ranks them by impact, and turns the highest-impact ones into fixes your team reviews rather than a list of anomalies someone has to triage. The distinction from a standard observability tool is that Agnost is reading the conversation as a user experience, not the trace as a system event — the failures it surfaces are the ones where nothing errored and the agent still lost the user. A second output falls out of the same analysis: unmet demand. One customer describes discovering 1,247 feature requests sitting inside chats they had already had, for features they didn't have and didn't know people wanted. The company also reports autonomous pull requests, with 16 of 18 merged at one customer, so the loop runs from production signal through to proposed code change. Public references are unusually concrete for an early company — a Google engineer describing observability integrated into MCP Toolbox for Databases, a member of technical staff at Exa on analytics and error-rate tracking, and a GTM lead at Corgi Insure reporting that voice BDRs booked more meetings once Agnost surfaced which conversation patterns actually converted.
Ideal use cases:
- •Teams or individuals who need continuous analysis of production conversations for stuck, frustrated, and non-converting users
- •Teams or individuals who need failure patterns ranked by impact instead of raw anomaly lists
- •Teams or individuals who need reviewed fixes and autonomous pull requests generated from production signal
- •Teams or individuals who need feature-request mining from conversations users already had
- •Anyone focused on agent analytics workflows
- •Anyone focused on conversation analysis workflows
Best for: EvalsHub
EvalsHub is an AI quality-assurance platform built around LLM-as-a-judge scoring, aimed at teams still catching regressions through manual spot-checks. You define rubrics as natural-language criteria with weights and thresholds — accuracy matched against ground truth, hallucination held above a confidence bar — and evaluations run continuously against your data, comparing models and flagging regressions before a release rather than after a user finds them. Results are deterministic scores rather than impressions, which is the stated point: the site frames it as bringing traditional engineering rigour to generative output, so you can compare GPT-, Claude- and Llama-family responses on the same rubric and see which passed and which hallucinated. Alongside evaluation there is an adversarial testing surface that red-teams the model automatically: heuristic and LLM-based detection of prompt injection hidden in user input, stress testing against evolving persona-based jailbreaks and DAN-style bypasses, and verification of content filtering, PII leakage and internal policy compliance. Tracing, datasets and experiments are the underlying units — spans, AI-generated dataset rows, experiments and projects — and CI/CD integration puts the whole thing in the release path. Pricing is published in full: a genuinely usable free tier, a $39/mo Pro tier that unlocks red-teaming, A/B prompt tests, online auto-evals and custom LLM judges, and a scoped enterprise tier.
Ideal use cases:
- •Teams or individuals who need natural-language rubrics with weights and thresholds
- •Teams or individuals who need llm-as-a-judge scoring tailored to specific use cases
- •Teams or individuals who need automatic regression detection and cross-model comparison
- •Teams or individuals who need red-team suite for prompt injection, jailbreaks and pii leakage
- •Anyone focused on llm-evals workflows
- •Anyone focused on llm-as-judge workflows
🤖 Other AI Agent Infrastructure Tools to Consider
Agnost AI and EvalsHub aren't the only options. Here are other popular tools in the same space:
SuperAGI
Open-source autonomous AI agent framework with visual dashboard — 14K GitHub stars
MetaGPT
Multi-agent AI framework simulating software teams — 45K GitHub stars, builds full apps from prompts
Cerebras
Fastest LLM inference powered by the Wafer Scale Engine.
Scale AI
AI data platform for training data and model evaluation.
Roboflow
End-to-end computer vision platform for developers.
Labelbox
Enterprise data labeling platform for ML training datasets.
Is one of these your tool?
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Frequently Asked Questions
Is Agnost AI better than EvalsHub?
It depends on your needs. Agnost AI offers 6 key features including Continuous analysis of production conversations for stuck, frustrated, and non-converting users and Failure patterns ranked by impact instead of raw anomaly lists, while EvalsHub provides 6 features including Natural-language rubrics with weights and thresholds and LLM-as-a-judge scoring tailored to specific use cases. Agnost AI uses a freemium model with a free tier, while EvalsHub is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is Agnost AI cheaper than EvalsHub?
EvalsHub is cheaper, starting at $39/month compared to Agnost AI's The site offers a self-serve 'try now' entry point and docs but publishes no tier pricing as of July 2026, so cost above the trial is a sales conversation.. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use Agnost AI and EvalsHub together?
Yes, many users combine Agnost AI and EvalsHub in their workflow. Agnost AI excels at continuous analysis of production conversations for stuck, frustrated, and non-converting users, while EvalsHub shines with natural-language rubrics with weights and thresholds. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between Agnost AI and EvalsHub?
While both are ai agent infrastructure tools, Agnost AI emphasizes continuous analysis of production conversations for stuck, frustrated, and non-converting users, whereas EvalsHub is known for natural-language rubrics with weights and thresholds. The best choice depends on your specific workflow and feature priorities.
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