Version comparison
Compare prompts, models, RAG setups, routing mechanisms, or other pipeline settings to see how changes affect LLM application performance.
Deepchecks
ClaimDeepchecks is a platform for LLM evaluation, testing, and monitoring to validate prompts, models, RAG pipelines, and agent workflows with hosted, private, or AWS-managed deployment.
LLM evaluation and monitoring platform
Deepchecks is a platform for LLM evaluation, testing, and monitoring. The pricing page describes it as a way to run continuous ML validation for AI applications, while the docs and AWS pages focus on validating prompts, models, retrieval setups, and multi-step agent workflows.
It is built for teams that need to compare versions, manage evaluation sets, automate or guide annotations, and monitor production behavior across individual AI applications. The platform is offered as a hosted SaaS product and also supports private, self-hosted, and AWS-managed deployment options.
Core capabilities
AI-assisted annotations
Use AI-assisted annotations to streamline manual review, with customizable scoring algorithms and learning techniques that adapt to your data.
EvalSet management
Generate, version, expand, and explore evaluation sets for a specific workflow, including ground truth creation and test-set style benchmarking.
Flexible evaluation properties
Choose from SLM-powered quality, risk, and policy metrics, plus LLM-powered custom metrics, technical metrics, and user feedback loops.
Usage monitoring
Track monthly DPU consumption in a usage dashboard and understand which workloads are driving platform usage.
Multi-lingual and managed evaluation
Evaluate applications in multiple languages and use built-in prompt-based evaluation without bringing your own LLM API keys.
Common workflows
Pre-release LLM validation
Validate a chatbot, assistant, or other LLM application before wider release by comparing prompt or model changes and reviewing evaluation outputs against ground truth.
Production monitoring for multiple apps
Operate several production AI applications with recurring evaluation and governance needs, using plan limits, retention, and usage tracking to keep teams aligned.
Multi-agent workflow evaluation
Assess multi-step agents that move through complex tasks, where teams need to inspect decision points, transitions, and failures across the workflow.
RAG quality assessment
Benchmark retrieval-augmented generation setups by building evaluation sets and measuring how well the system uses external sources and answers with context.
Task-specific model testing
Review summaries, generated text, classification behavior, or natural-language-to-code outputs with custom metrics and guided annotation workflows.
Pros and Cons
Pros
- Covers the workflow from evaluation-set creation through version comparison and production monitoring.
- Supports multiple deployment models, including hosted, VPC, bare-metal, and AWS-managed options.
- Includes built-in evaluation properties for quality, risk, policy, technical, and feedback-driven checks.
- Provides AI-assisted annotation tools and customizable scoring to reduce manual review effort.
- Supports multiple languages and does not require external API keys for prompt-based evaluations.
Cons
- The public pricing page shows plan structure and usage limits, but the exact commercial pricing is not listed on the page text provided.
- Some deployment and compliance details are only described at a high level, so buyers with strict requirements still need to confirm certifications and architecture specifics directly.
FAQ
Which plan should I choose?
Deepchecks is positioned for teams validating and monitoring LLM applications and agent workflows. The pricing page says Basic fits early-stage validation and single-application setups, Scale fits multiple production applications and multi-step agents, and Enterprise fits business-critical deployments with advanced security and control.
Can I change plans later?
For SaaS deployments, upgrades are available during the contract term. Paid plans also allow additional users or AI applications, and downgrades typically take effect at the next renewal.
Are user licenses transferable?
Yes. Seats can be reassigned to different users within the organization through workspace administration.
What does Deepchecks mean by an AI Application?
An AI Application is a distinct LLM-powered system or workflow you evaluate and monitor in Deepchecks. Examples given on the pricing page include customer-facing chatbots, internal AI assistants, RAG pipelines, and multi-agent workflows.
Does Deepchecks support private or self-hosted deployments?
Deepchecks supports VPC deployments on AWS, GCP, or Azure, bare-metal deployments, and an AWS-managed option. The pricing page also notes a hosted SaaS model and a privately hosted option.
Quick Facts
- Category
- LLM evaluation, testing, and monitoring
- Platform
- Hosted SaaS, privately hosted, VPC, bare-metal, and AWS-managed deployment options
- Primary users
- Teams building and operating LLM applications and AI agents
- Source domain
- deepchecks.com
- Pricing model
- Tiered plans with trial/demo/contact flows; fixed quotas and add-on capacity for SaaS usage
- Key workflow
- Version comparison, annotation, EvalSet management, properties, and monitoring