Hydrolix brings high-speed analytics to petabyte-scale agentic AI
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.
Key Takeaways
- AI-ready data for agentic AI: Hydrolix delivers real-time analytics, petabyte-scale queries, and subsecond response times via AWS Marketplace.
AI Hydrolix brings high-speed analytics to petabyte-scale agentic AI Mark Albertson June 16, 2026 4 MIN READ link reply The mission behind data management provider Hydrolix Inc.
- "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.
- 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.
- "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.
- 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.
AI-ready data for agentic AI: Hydrolix delivers real-time analytics, petabyte-scale queries, and subsecond response times via AWS Marketplace. AI Hydrolix brings high-speed analytics to petabyte-scale agentic AI Mark Albertson June 16, 2026 4 MIN READ link reply 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.
For more details please read the original article at SiliconANGLE AI.
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