PuppyGraph, a Santa Clara-based graph query engine startup, said it has raised $10 million in a Series A round led by Particle Future and defy.vc. The new funding follows the general release of version 1.0 of its software and will go toward building out the company's enterprise go-to-market operation and engineering, according to the company. The round marks the second time defy.vc has led a round for PuppyGraph, after a $5 million seed round in November 2024. Investors have now put $15 million into the startup.
PuppyGraph's query engine lets companies treat data already stored in their warehouses and lakehouses as a single graph, without moving it into a separate graph database first. The company says AI agents running on the software can work across 3,000 enterprise tables and return graph query results in under a second. Setup begins with an AI-assisted tool that drafts a schema from a customer's existing tables; once users approve it, they can ask questions of the graph in plain English. PuppyGraph offers its own agent for this, and the Model Context Protocol lets companies bring in the AI tools they already use.
According to PuppyGraph, agent projects often run into trouble after the pilot stage. The company's own example asks which critical systems an attacker could reach from a compromised account, a question that requires tracing how identities and permissions connect across thousands of tables in several systems. A proof of concept might cover 30 to 50 tables, and teams that scale past that find schema descriptions alone consuming an agent's context window, while queries running several relationships deep can stall until they time out. PuppyGraph keeps agents from guessing how data fits together: any agent that references a relationship nobody set up has its query rejected, and the returned error is written for the agent to act on.
When PuppyGraph connects to Snowflake Inc. or Databricks Inc., it can obtain short-lived credentials tied to the user's identity, so nobody has to hand over long-lived keys. Row-level permissions configured on the data still apply, and the company says it checks them at each hop of a traversal. Weimo Liu, co-founder and chief executive of PuppyGraph, said the insights of enterprise data will soon be generated by agents, with users expecting to ask questions that cross departments and systems beyond the workflows built into a dashboard. Liu worked as a software engineer at Google LLC before co-founding the company.
PuppyGraph's customer list includes Advanced Micro Devices Inc. and Palo Alto Networks Inc., and the announcement also named Coinbase Global Inc., Datadog Inc. and Trend Micro Inc. as customers. Xinyu Liu, a staff software engineer at Coinbase, said that because the exchange connects straight to tables it already keeps in Snowflake and Databricks, standing up a new graph is a schema definition rather than a data migration. PuppyGraph said its annual recurring revenue grew sevenfold over the past year, by the startup's count; no dollar figure was disclosed.
Amy Yin, a partner at defy.vc, said writing a query is now a job a user can hand to Anthropic PBC's Claude, but executing it across billions of relationships still takes serious engineering. Developers can download a free version of PuppyGraph with a single Docker command and no sign-up form, and the company says it takes about 10 minutes to go from deployment to a first query.
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