Adept vs Confident AI

What is Adept?

Adept is an AI DevTool designed to enhance technology stacks by accelerating agent development and improving workflows with proven results.

Who is Adept for?

Adept is primarily for professionals in supply-chain management, financial services, and healthcare, looking to streamline processes and improve operational efficiency.

What can I do with Adept?

With Adept, you can translate user intents into actions, accurately locate items on web pages or applications, and plan and execute complex enterprise workflows.

How much does Adept cost?

Adept publishes a custom / contact-sales pricing model — get a quote on their site.

How is Adept different from alternatives?

Adept focuses on agent development within the AI DevTools category, providing specialized features like proprietary agent training data and custom actuation software for enhanced automation.

How is this different from DeepEval?

DeepEval is the open-source evaluation framework that powers the metrics and testing logic. Confident AI is the platform layer that adds collaboration, visualization, dataset management, production tracing, and team workflows on top. Think of DeepEval as the engine, and Confident AI as the full vehicle — you get dashboards, experiment tracking, human-in-the-loop workflows, and production observability all in one place.

What LLM use cases are supported?

All types of LLM use cases are supported, including summarization, Text-SQL, customer support chatbots, internal RAG QAs, conversational agents, and more. These can be any architecture — RAG pipelines, agentic workflows, conversational chatbots, or combinations like RAG chatbots and agentic RAG systems. Confident AI has tailored metrics and capabilities for different application types. Your evaluation strategy should match your use case. Learn more about supported use cases here.

What about complex agentic systems?

Complex agentic systems are fully supported through LLM tracing. Tracing gives you visibility into every step of agent execution — tool calls, reasoning chains, and intermediate outputs. One important consideration: be intentional about what you evaluate. Trying to measure everything often means you’re measuring nothing useful. Focus on the outputs and behaviors that matter most for your users.

Who uses Confident AI?

Our platform is designed for cross-functional AI teams: - Engineers use evals in CI/CD and traces for debugging - QAs build test datasets and run regression suites - PMs track quality metrics and compare experiments - SMEs & Annotators label data and review AI outputs in human-in-the-loop workflows

Is Confident AI enterprise ready?

Yes. We offer SSO, team-based data segregation, customizable user roles and permissions, and self-hosted deployment options for your cloud environment.