AI Agent QA and Observability Stack
This is the stack for teams who are past demos and now need to see what their agents are doing in production, test behavior before launch, and compare model changes without flying blind.
1 saves
Loading
An AI agent stack for building, testing, and shipping agents with tools, memory, browser actions, and evals without turning the setup into a huge mess.
Workflow stack
The order matters. Start at the top, read down the sequence, and open any step when you want the note behind it.
Model routing
Lets you swap and route models without rebuilding your stack each time. Useful when you want flexibility on cost, speed, or model choice.
Open tool profileBrowser actions
Handles the web side of an agent stack. Good when your agent needs to click, browse, extract info, or complete tasks inside real websites.
Open tool profileMemory layer
Gives the agent memory so it can keep useful context across tasks and sessions instead of acting like every run is the first one.
Open tool profileEvals + testing
You need a way to test prompts and agent behavior before trusting it. This gives you a cleaner way to compare runs and catch regressions early.
Open tool profileDeployment
Good final layer for running and shipping the agent. It helps you move from local experiments to something people can actually use.
Open tool profileTools in this stack
Open any tool profile if you want pricing, fit, or comparison details.
Pydantic's open-source GenAI agent framework for typed Python agents, structured outputs, retries, tools, and provider integration.
Related stacks
Open-source SDK and AI gateway for routing across many LLM providers through a unified OpenAI-compatible interface, with an enterprise tier for security and operations.
Hosted browser-agent platform with cloud sessions, agent models, skills, and pricing built around real browser automation workloads.
A memory layer for AI applications that helps agents and copilots retain useful context across sessions.
Evaluation and testing toolkit for prompts, models, and LLM application behavior.
Cloud runtime for running Python jobs, AI workloads, and scalable compute from code.
Compare tools in this stack
Official StackBased Editorial Postings
