Oliver AI has raised pre-seed funding from Menlo Ventures and Unusual Ventures to scale OliverDB, its high-performance analytical data platform designed specifically for agentic AI workloads.
Oliver AI is targeting a growing infrastructure challenge created by AI agents.
Traditional enterprise analytics platforms were largely built around workloads generated by people and conventional applications. AI agents can instead generate continuous, unpredictable analytical workloads at machine speed, potentially increasing both infrastructure requirements and computing costs as deployments expand.
OliverDB is designed to allow AI agents to analyze enterprise data in real time while reducing the computing resources required to perform those workloads.
In internal tests using query shapes from ClickBench, Oliver said its platform ran hundreds of times faster than ClickHouse using CPUs and thousands of times faster when using GPU execution. The company noted that the results were based on its own testing, are dependent on workload and configuration, and have not been independently audited.
Oliver AI is also addressing governance, observability, and access control for enterprise AI agents.
OliverDB provides governance across enterprise databases and Model Context Protocol servers. Organizations can create policies defining which information an agent can access and which actions it is permitted to take while maintaining an attributable record of agent interactions.
Another component of the platform is Oliver’s model swarm.
Rather than depending on one model to produce an answer, the system can run multiple smaller specialized models in parallel to examine competing hypotheses and alternative explanations. A conductor model evaluates those results and returns the conclusion it determines is best supported by available data, including returning no conclusion when the evidence is insufficient.
The approach is designed to provide more extensive analysis while reducing token usage and limiting the need to use more expensive frontier models for every task.
OliverDB is currently available for enterprise deployments as either a managed service or within a customer’s virtual private cloud.
KEY QUOTES:
“This is not a 25% or 50% improvement to existing analytics infrastructure. It’s a complete step change. A multi-petabyte analytics environment which requires thousands of servers today can collapse down to just a couple of servers, or even a single GPU, on Oliver, while simultaneously delivering dramatically faster performance. That changes what AI agents can do, how quickly they can do it, and the economics of operating them at enterprise scale.”
Praneet Sharma, Co-Founder of Oliver AI
“Snowflake and Databricks helped define new categories of data infrastructure for the cloud era. Agentic AI represents another fundamental shift. Oliver represents a new kind of infrastructure designed specifically for the needs of agentic AI, combining the performance, efficiency, and control enterprises need to deploy AI agents at scale.”
Tim Tully, Partner at Menlo Ventures
“The challenge in enterprise AI is no longer simply whether a model is capable enough. The challenge is giving AI systems meaningful access to valuable enterprise data without sacrificing control, reliability, or trust. Oliver combines the performance, governance, and grounded intelligence required to deploy those systems in the real world.”
John Vrionis, Founder at Unusual Ventures
