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.
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For teams that want internal AI chat and document workflows without handing everything to a public SaaS assistant. This stack leans into self-hosting, local models, and controlled access to stronger remote models when needed.
Workflow stack
The order matters. Start at the top, read down the sequence, and open any step when you want the note behind it.
Run local models
Keeps a lot of day-to-day model usage local, which is why it shows up so often in self-hosted AI setups.
Open tool profileBuild knowledge spaces
Adds private document chat and workspace structure instead of leaving the stack as a generic model playground.
Open tool profileParse messy files
Important when the quality of PDFs and complex docs determines whether the internal assistant is actually useful.
Open tool profileReach bigger models
Gives the team model flexibility for harder tasks without locking the whole stack to one provider.
Open tool profileTools in this stack
Open any tool profile if you want pricing, fit, or comparison details.
Self-hosted chat interface for local and remote LLMs with private deployment and team friendly controls.
Local and cloud runtime for open models with a strong developer UX, simple APIs, desktop apps, and a newly clearer commercial pricing ladder.
Related stacks
Private AI workspace for document chat, knowledge bases, and agent workflows across local or hosted models.
A document parsing API from LlamaIndex for turning complex files into LLM-ready structured output.
Unified API for accessing and routing across many language models and providers with one integration layer.
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