Pylar
Hey HN! We're Hoshang & Vishal, the team behind Pylar - a governed access layer between databases and LLMs. We previously led data and AI and we kept seeing the same problem across teams using LLMs internally: agents are great with unstructured data, but the moment you want them touching your actual systems of record — Snowflake, Postgres, CRMs, product DBs — everything becomes fragile, risky, or outright unsafe. Two issues show up every single time: 1. Agents over-querying They don’t understand cost. They’ll happily generate queries that blow up your warehouse bill. 2. Accidental data…
Pylar launched on December 4, 2025 with 502 votes, #18 of 11,628 launches that month and more than 99% of that year's launches.
In plain words
Pylar is a platform that enables secure connections between AI agents and data sources. It allows developers to connect agents to any datasource, set specific data access permissions, convert those authorized views into custom Model Context Protocol tools, and deploy them across different agent builders. The platform includes observability features to monitor all AI deployments, making it suited for teams managing multiple AI agents that need controlled access to enterprise data.
written from the facts on this page · September 2026
From the sources
Pylar connects agents to your data stack, safely. Connect to any datasource, define exactly what an agent can see, turn those views into custom MCP tools, and publish them to any agent builder - with full observability across every AI deployment.
Give AI agents safe access to structured data. Create governed SQL views, build MCP tools, and deploy to any agent builder. Secure, scalable, and fully controlled data access for AI applications.
Pylar sits between your agents and your databases. You define what data they can access, build custom tools on top of it, and get full observability across all your AI deployments. Creating MCP tool from `cs_support` view... ```json { "name": "get_customer_health", "description": "Get customer health status and metrics by email", "params": { "email": "string" }, "query": "cs_support_by_email(@email)" } ``` ✅ Published to MCP tools Trusted by teams shipping production AI Security wouldn't let us hook agents straight into Snowflake. Can't say I blame them honestly. Pylar fixed it though. We just tell it what's safe to share, agents get what they need, and our compute costs stay predictable.…from pylar.ai
In the maker’s words, at launch
Hey HN! We're Hoshang & Vishal, the team behind Pylar - a governed access layer between databases and LLMs. We previously led data and AI and we kept seeing the same problem across teams using LLMs internally: agents are great with unstructured data, but the moment you want them touching your actual systems of record…
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