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Deepchecks is an end-to-end platform for evaluating, validating, and monitoring LLM-based applications. It helps AI teams define, measure, and validate AI progress, ensuring the release of high-quality, reliable applications by streamlining testing from development through CI/CD to production.

5.0
Added
2025-08-11
Price type:
Freemium
Monthly traffic:
78.6K

deepchecks Overview

Deepchecks is a comprehensive LLM evaluation platform designed to address the complex and subjective nature of testing and validating AI applications. Founded by machine learning experts who experienced the challenges of silent model failures firsthand, Deepchecks provides a robust solution for organizations to gain control over their ML systems. The platform enables teams to release high-quality LLM apps quickly and confidently by standardizing performance metrics, providing credible auto-scoring, and streamlining version comparisons.

The core challenge with LLM applications is the absence of a traditional test set, making performance measurement difficult. A minor change in a prompt or model can drastically alter the output's meaning. Deepchecks tackles this by offering an all-inclusive platform that transforms evaluation from a complex project into a streamlined, repeatable process. It helps teams move beyond basic LLM-as-a-judge techniques, which often require significant DIY effort and lack accuracy and consistency.

How to use deepchecks

Using Deepchecks involves integrating its evaluation capabilities throughout the entire lifecycle of an LLM application:

  1. Setup & Integration: Connect Deepchecks to your development environment. It offers multiple deployment options, including multi-tenant SaaS, single-tenant SaaS, and on-premise solutions to meet various data privacy and security requirements. It also provides native integrations with popular MLOps stacks like AWS SageMaker.
  2. Define Evaluation Metrics: Configure an automated scoring pipeline tailored to your application's specific needs. This involves setting up nuanced constraints and defining what constitutes a 'good' response.
  3. Generate Datasets: Leverage the platform to generate relevant test datasets and create LLM judges within minutes to assess performance against your defined criteria.
  4. Compare Versions: Systematically compare different versions of your prompts, models, or even complex agentic workflows. Deepchecks provides clear, data-driven insights to help you choose the best-performing version.
  5. Automate Testing in CI/CD: Integrate Deepchecks into your Continuous Integration/Continuous Deployment (CI/CD) pipeline to automatically test every new version of your LLM app before it reaches production, catching regressions and quality issues early.
  6. Monitor in Production: Once deployed, use Deepchecks to continuously monitor your application's performance, detecting issues like hallucinations, data drift, or degradation in response quality over time.

Core Features of deepchecks

  • End-to-End LLM Evaluation Platform: A single, all-inclusive solution for testing, validation, and monitoring, from development to production.
  • Swarm of Evaluation Agents: Utilizes a sophisticated algorithmic backbone of small language models (SLMs) and multi-step NLP pipelines working together using Mixture of Experts (MoE) techniques to simulate an intelligent human annotator, ensuring superior accuracy.
  • Customizable Auto-Scoring: Set up automated scoring pipelines to evaluate generated text based on nuanced, user-defined constraints.
  • Comprehensive Version Comparison: Compare performance across different versions of prompts, models, agents, and entire AI systems.
  • Dataset Generation & LLM Judges: Quickly create synthetic datasets and configure LLM-based evaluators for robust testing.
  • CI/CD and Production Monitoring: Seamlessly integrate with CI/CD pipelines for pre-deployment testing and monitor live applications for performance degradation.
  • Flexible Deployment & Security: Offers multiple deployment options (SaaS, On-Prem, AWS GovCloud) and is compliant with SOC2 Type 2, GDPR, and HIPAA.

Use Cases for deepchecks

Deepchecks is ideal for various scenarios across the AI development lifecycle:

  • AI Development Teams: For developers and ML engineers building and iterating on LLM-based applications like RAG systems, chatbots, or content generation tools.
  • Enterprise AI Adoption: For large organizations scaling their LLM applications to production and needing to ensure reliability, safety, and consistent performance.
  • Quality Assurance: For QA teams tasked with validating the subjective and complex outputs of generative AI models.
  • MLOps Engineers: For professionals looking to build robust, automated MLOps pipelines that include continuous testing and validation for ML models.
  • Risk and Compliance: For teams needing to mitigate risks associated with AI, such as hallucinations, biased outputs, and low-quality responses, to maintain brand reputation and user trust.

Advantages of deepchecks

Deepchecks offers significant advantages over manual testing or fragmented open-source tools:

  • Accelerated Time-to-Production: By automating and streamlining the evaluation process, it dramatically reduces the time it takes to confidently deploy new LLM applications.
  • Improved Quality & Reliability: Systematically reduces hallucinations and low-quality responses by providing objective, repeatable measurements.
  • Data-Driven Decisions: Enables teams to make informed, data-backed decisions when comparing different model or prompt versions.
  • Scalable & Future-Proof: The platform is designed to scale with your needs and stay ahead of the curve, solving today's problems and those that will arise in the future.
  • Enhanced Security and Privacy: With flexible deployment options and enterprise-grade compliance, it accommodates the strictest data security constraints.

Pricing and Plans

Deepchecks offers flexible pricing plans designed to scale with your needs, available in both Cloud-Hosted and Privately-Hosted options.

  • Basic: Ideal for small teams and startups. This plan is available as a free trial and includes up to 3 seats, 1 AI application, up to 5K DPUs/month, and 3 months of data retention.
  • Scale: Designed for teams with several production-grade AI applications. It includes all features from the Basic plan, plus 5 seats, 3 AI applications, 20K DPUs/month, premium support, and guided onboarding. Pricing is available upon requesting a demo.
  • Enterprise: A custom plan for companies with high data volumes and advanced security needs. It includes all features from the Scale plan, plus custom seats and application limits, custom DPUs, enterprise-grade security, and a dedicated customer success team. Contact sales for pricing.

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Traffic

Latest traffic

Monthly visits78.6K
Avg visit duration0:48
Pages per visit2.05
Bounce rate43.0%

Status

Falling-5.3%vs previous month
Updated at 2026-06-15

Monthly traffic trend

  • 2025-9: 109.5K
  • 2026-1: 119.8K
  • 2026-2: 102.1K
  • 2026-3: 92.4K
  • 2026-4: 83.0K
  • 2026-5: 78.6K

Geography

Top 5 countries / regions

  • ๐Ÿ‡บ๐Ÿ‡ธUnited States
    26.3%
  • ๐Ÿ‡ฌ๐Ÿ‡งUnited Kingdom
    21.0%
  • ๐Ÿ‡ป๐Ÿ‡ณVietnam
    19.8%
  • ๐Ÿ‡ฎ๐Ÿ‡ณIndia
    18.4%
  • ๐Ÿ‡ณ๐Ÿ‡ฌNigeria
    14.5%

Traffic sources

Source typePercentage
Direct
63.5%
Referral
35.7%
Email
0.8%
Total
100%
Direct63.5%
Referral35.7%
Email0.8%

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KeywordCost per click
deepchecks$0.70
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nvdia nim$0.00
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snippets mock data$0.00

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