One of the biggest blockers to building agents is getting the data 'agent-ready'. Teams spend months building pipelines, wiring up sources, cleaning data, and centralizing it - before an agent can even ask its first question.
Pylar now does this out of the box.
We re source-agnostic. Whether your data lives across multiple databases and warehouses (Supabase, Snowflake, MySQL, etc.), you can connect one or many instantly, no re-architecture required.
If you don't have a warehouse yet, we ve got you covered. Pylar ships with 100+ built-in integrations across marketing tools, CRMs, support platforms, product databases, and billing systems. Data comes in cleaned, transformed, and centralized, ready for agents to work with.
Next up is agent views - once you've connected to your sources, you can write SQL across or within to create precise, sanitized, sandboxed views purpose built for specific agents.
Agents don t roam your databases arbitrarily. You deterministically scope exactly what fields they can access, so they do their job well, without hallucinating or giving you different answers for the same/similar questions.
Give it a try and let me know what you think!
SyncSignature
Pylar
@neelptl2602 Thanks Neel!
Argil
amazing product guys well done !!
Pylar
@othmane_khadri Thank you for your support!
congratulations for your product!!
Pylar
@madalina_barbu Thanks!
Nas.io
How do you monitor agent behavior across different builders (Cursor, LangGraph, n8n, etc.) from one place?
Pylar
@nuseir_yassin1 Our evals layer helps you measure how different agents across platforms like Cursor, LangGraph etc are interacting with your internal data.
Because of that, you get a single place where you can see:
what each agent is querying
how often it’s hitting your data
what was allowed vs blocked
and any odd behavior you should know about
So even if one agent is in Cursor and another is in LangGraph or n8n, all their activity shows up in one dashboard.
Also, if you update a data view, a rule or add more mcp tools in Pylar - every agent using it automatically follows the new version.
More on this here - https://docs.pylar.ai/learn/evals/evals-dashboard
Does this help?
bunny.net
congrats on the launch!
Pylar
@marek_nalikowski Thank you!
This tool caters to teams building or deploying AI agents: it lets agents leverage internal data (to deliver context-rich outputs) while maintaining strict control over data access—addressing both efficiency and risk management needs.
Do you plan to expand compatibility to niche or industry-specific datasources (e.g., healthcare EHR databases, financial ledger systems) for specialized use cases? Also, will Pylar include pre-built access control templates aligned with common compliance frameworks (e.g., HIPAA, GDPR) to accelerate secure setup for regulated industries?
Excellent tool for process automation. Congratulations on the launch!
Pylar
@mykyta_semenov_ Thank you!