PuppyGraph lands $10M to let AI agents query data without moving it
What's the deal? PuppyGraphDealroom has a profile for this one. Try Dealroom →, a graph query engine for enterprise AI agents, has raised a $10 million Series A led by Particle FutureDealroom has a profile for this one. Try Dealroom → and Defy.vc, chief executive officer Weimo Liu told Axios. The round brings total funding to $15 million after a $5 million seed in 2024.
What's the endgame? PuppyGraph lets AI agents query connected enterprise data as a single federated graph — at petabyte scale and subsecond speeds — without loading it into a separate graph database. The company says its 1.0 release can query 3,000 tables in subseconds.
Why now? AI agents need fast, accurate access to enterprise data to deliver useful answers. The raise follows the availability of PuppyGraph 1.0 and will fund engineering and enterprise go-to-market expansion.
By the numbers: PuppyGraph lists customers including AMD, Palo Alto Networks, Datadog, Coinbase, Trend MicroDealroom has a profile for this one. Try Dealroom →, and Baker HughesDealroom has a profile for this one. Try Dealroom →. Annual recurring revenue grew 7x over the past year, it said.
What could go wrong? The competitive landscape is strengthening. Neo4j recently launched a Context Engine and partnered with IBM to fold knowledge graphs into enterprise AI stacks, putting established players squarely in PuppyGraph's path.
The signal: The round is a bet on querying data in place rather than duplicating it — a real trade-off as companies try to give agents useful context without the cost of moving data. PuppyGraph's performance and adoption claims, however, remain its own.
Read more: Axios
Image credit: U.S. Army Combat Capabilities Development Command
