Everything you need to build, govern, and scale data and AI workloads—one unified platform.

Monitor, detect, and resolve data and AI issues with end-to-end observability across pipelines.
Build, orchestrate, and run data pipelines with intelligent agents that automate the entire engineering workflow.
Query your lakehouse in-place with Velox-accelerated performance. 10x faster than traditional warehouses.
Distributed training, high-throughput inference, and GPU notebooks—everything you need for production AI.
Build, deploy, and manage intelligent agents to automate and optimize data operations.
An open-source data platform for Hadoop modernization, flexibility, and long-term control.
AI-powered observability and optimization for Hadoop and big data environments.
Browse solutions to help you solve the complex business challenges unique to your industry.
"PhonePe’s data infrastructure reliability initiative would never have been possible without Acceldata.”
Browse materials to help you access the tools, guides, and insights essential to your workflows.
How to assess AI data readiness across four stages.
Learn about our mission, leadership, and vision driving modern data operations forward.
How to assess AI data readiness across four stages.
Browse solutions to help you solve the complex business challenges unique to your industry.
"PhonePe’s data infrastructure reliability initiative would never have been possible without Acceldata.”
Browse materials to help you access the tools, guides, and insights essential to your workflows.
How to assess AI data readiness across four stages.
Learn about our mission, leadership, and vision driving modern data operations forward.
How to assess AI data readiness across four stages.
Everything you need to build, govern, and scale data and AI workloads—one unified platform.

Monitor, detect, and resolve data and AI issues with end-to-end observability across pipelines.
Build, deploy, and manage intelligent agents to automate and optimize data operations.
Build, orchestrate, and run data pipelines with intelligent agents that automate the entire engineering workflow.
Query your lakehouse in-place with Velox-accelerated performance. 10x faster than traditional warehouses.
Distributed training, high-throughput inference, and GPU notebooks—everything you need for production AI.
An open-source data platform for Hadoop modernization, flexibility, and long-term control.
AI-powered observability and optimization for Hadoop and big data environments.
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Monitor, detect, and resolve data issues with end-to-end observability across pipelines.
Monitor, detect, and resolve data issues with end-to-end observability across pipelines.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse sollicitudin mi nibh
AI-powered observability and optimization for Hadoop and big data environments.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse sollicitudin
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse so
An open-source data platform for Hadoop modernization, flexibility, and long-term control.
Hard to monitor pipeline failures manually? Acceldata’s shift-left approach monitors pipelines from landing zone to consumption
Seamlessly integrate your tech stack handling all stages of your data easiter, faster, effective

Build, manage, and optimize data pipelines across hybrid environments with full visibility.
Monitor, detect, and resolve data issues with end-to-end observability across pipelines.
An open-source data platform for Hadoop modernization, flexibility, and long-term control.
Build, manage, and optimize data pipelines across hybrid environments with full visibility.
Build, manage, and optimize data pipelines across hybrid environments with full visibility.
An open-source data platform for Hadoop modernization, flexibility, and long-term control.
Browse solutions to help you solve the complex business challenges unique to your industry.
"PhonePe’s data infrastructure reliability initiative would never have been possible without Acceldata.”
Browse materials to help you access the tools, guides, and insights essential to your workflows.
How to assess AI data readiness across four stages.
Learn about our mission, leadership, and vision driving modern data operations forward.
How to assess AI data readiness across four stages.
Your team spends 30% of their week just finding and vetting data assets. The Catalog Agent ends that—discovering, classifying, and governing 1,000+ assets automatically, so engineers build instead of search.



Three capabilities that turn a passive metadata store into an active intelligence layer for your entire data estate.
Every classification, policy, and certification the agent proposes is yours to review, override, or approve—before it goes live.
The hardest part is validating that every row, every pipeline, every layer landed correctly. That's what this agent is built for.
From first scan to governed catalog—in a single agentic loop.
Powered by the xLake Reasoning Engine, the Catalog Agent runs as part of a multi-agent framework that coordinates discovery, enrichment, and policy deployment in parallel—delivering complex multi-system responses in record time.
Traditional catalogs are passive repositories—you populate them, maintain them, and hope teams use them. The Catalog Agent is autonomous: it discovers assets you didn't know existed, infers meaning from usage patterns, and deploys governance policies without human configuration. It's a living system, not a database you fill in.
Yes—and we have the receipts. What previously took 4–5 weeks per domain now completes in under a day. The agent discovers, profiles, classifies, and queues governance policies for 1,000+ assets in a single run. Human-in-the-loop checkpoints let your team review before anything goes live.
The agent uses pattern recognition and semantic analysis to identify PII, financial, and health-related columns automatically. It then applies sensitivity tags, access controls, and retention rules aligned with GDPR, HIPAA, and SOC 2. Every classification is reviewable by your data stewards before enforcement kicks in.
No. The Acceldata Dataplane runs inside your security perimeter. Only metadata and contextual information are sent to the configured LLM—never raw data or dataset contents. No customer data is persisted in the LLM. You can also use BYO LLM to point ADM at a model hosted entirely within your own infrastructure. All activity is logged for audit purposes under your existing RBAC and encryption policies.
An AI-ready asset has four things verified: documented ownership, end-to-end lineage, active quality monitoring, and appropriate governance policies. The Catalog Agent checks and certifies all four. Teams using ADM go from accessing 30% of their data platform features through a traditional UI to 70%—because conversational access removes the technical barriers that kept non-engineers out of their own data estate.
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