Keep your LangChain and LangGraph spans. Confident AI scores every trace, span and thread, builds your datasets from production, catches drift and simulates conversations. Switch in three steps.
LangSmith traces LangChain and LangGraph in full. Move a component to another framework, or hand-roll an agent, and the trace loses its shape. Confident AI gives 16 frameworks the same depth and the same evals.
“Thanks to Confident AI, we were able to move to a fine-tuned model and cut our LLM costs by 80%. This opens up whole new use cases now to generate better output with more targeted LLM calls.”
Online evaluators on LangSmith are prompts and code an engineer writes and maintains. Product and QA wait. Confident AI ships 50+ metrics and lets non-engineers run experiments over HTTP.
“Before Confident AI, a single improvement cycle took 10 days — I'd create a task, assign it to an engineer, wait for availability, and go back and forth. Now the same cycle takes three hours, and our product managers can run it themselves.”
LangSmith runs and threads are logs. There is no way to simulate a user, run the whole conversation and score it before release. Confident AI does that on every release.
“We run a lot of large-scale, multi-turn simulations, and Confident AI made it far easier to design scenarios and execute those tests without piecing together external tools.”
See what changes for your team. Compare workflows for PMs, engineers, QAs, and SMEs.
| Feature | Confident AI | LangSmith |
|---|---|---|
Validate evals Check automated scores against human judgment | ||
Surface issues automatically Find recurring failures from production feedback | ||
Find product insights Understand patterns in real conversations | Not assessed | |
Find struggling users See which users experience failures and poor responses | Not assessed | |
Cross-functional workflows PMs and QA run evals without engineering |
FinomBefore Confident AI, a single improvement cycle took 10 days — I'd create a task, assign it to an engineer, wait for availability, and go back and forth. Now the same cycle takes three hours, and our product managers can run it themselves.
Confident AI saves us 480+ hours of manual AI evaluation every month — and gives us the data to defend every quality decision in front of engineering, product, and leadership.
Confident AI gave our team one place to turn production failures into datasets, align metrics, and keep regressions out of releases without waiting on custom engineering work.
HumachWe run a lot of large-scale, multi-turn simulations, and Confident AI made it far easier to design scenarios and execute those tests without piecing together external tools.
Thanks to Confident AI, we were able to move to a fine-tuned model and cut our LLM costs by 80%. This opens up whole new use cases now to generate better output with more targeted LLM calls.
