The mission behind data management provider Hydrolix Inc. is fairly simple: to build the next generation of AI tools and provide AI-ready data for enterprises.

Hydrolix’s approach is designed to feed the growing agentic infrastructure. This is not simple, because agents demand millisecond response times and access to complete datasets for accuracy and timely decisions. Meeting those requirements calls for insights from petabyte-scale datasets. Hydrolix’s solution ingests information in real time while providing cost-efficient data retention and sub-second query response times to support agentic AI.

“When you’re talking about AI and how you can extract information out of data, how you can build models, it’s actually really important to have all the data,” said Catherine Johnson (pictured), vice president of global solutions engineering at Hydrolix. “When it comes to agentic AI, what we really are is a way to store all of that data so that you can ask it questions using natural language to get answers across the full dataset, not just parts of it. You really get a full picture of what’s happening.”

Johnson spoke with Christophe Bertrand, principal analyst at theCUBE Research, for the AWS Marketplace Series on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed Hydrolix’s addition to AWS Marketplace and how the company delivers real-time analytics for insights in seconds. (* Disclosure below.)

High-speed AI-ready data

Hydrolix employs a built-in stream processing engine that can analyze data rapidly. Using advanced indexing, query and compression techniques in object storage, the company has developed a format and data retrieval platform that can deliver sub-second query latency across the entire data footprint. Massively parallel compute is applied to the object store, breaking data analysis tasks into smaller, rapidly executed subtasks.

“The solution sits in object storage; however, we can get sub-second latency on queries going out to the system and looking at tons and tons of data,” Johnson explained. “We’ve set up different skills and different agents that know how to go and look at data that we’ve held. The goal is that we’re getting information back really quickly.”

Hydrolix recently demonstrated what data access and visibility can look like in a case study with partner Nvidia Corp. Using Hydrolix’s MCP server, a Nvidia engineer was able to resolve a live content delivery network incident in nine minutes.

“What Nvidia was able to do with our MCP server was very quickly use natural language querying effectively to go ask their dataset for answers about what’s going on, what’s happening right now and then get an answer back so they could then mitigate the problem,” Johnson said. “It wasn’t, in that case, even just about how fast we can return the data. That natural language query part of it is really what brought the speed to that use case.”

Hydrolix’s availability through AWS Marketplace allows users to provision the solution, including its cloud infrastructure, customer projects and ingest endpoints. Hydrolix serves as a natural data layer for customers building agentic AI applications with Amazon Bedrock, and it can be especially helpful for media clients managing content delivery networks and web applications, according to Johnson.

“With AWS, our initial integrations have really been around the media space,” Johnson said. “It’s CDN, a lot of elemental services, web application firewall where we can bring a lot of data together into one place. We typically do it by having it all in a dataset so you can look at all of the data in a single stream and get answers back really quickly.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the AWS Marketplace Series:

(* Disclosure: TheCUBE is a paid media partner for the AWS Marketplace Series. Neither AWS, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE