Scale Operations with Autonomous AI Agents
Deploy intelligent agents that connect your data, automate workflows, and drive growth autonomously.
The Dataverses Next-Gen Intelligence Platform
Empowering your organization to build and deploy AI-driven solutions at scale.
Real-Time Intelligence
Unlock instant insights from streaming data without sacrificing accuracy or governance. Process events as they happen and act in the moment.
Democratize Data Access
Empower every team member to explore and analyze data using intuitive tools and natural language, bridging the gap between data and decision-makers.
Reduce Complexity
Consolidate your data stack into one unified platform. Eliminate silos, reduce maintenance overhead, and significantly cut infrastructure costs.
Streaming Data Lakehouse + AI
Enabling your organization to create and launch AI-powered solutions that scale.
From Stream to Lakehouse, Seamlessly
Transform streaming data into structured lakehouse storage with declarative pipelines. Simple YAML configurations that automatically scale, monitor, and maintain complete data lineage from source to destination.
Frequently Asked Questions
Everything you need to know about Dataverses and how it can transform your data analytics workflow
Dataverses is a unified streaming data platform that combines real-time data processing, lakehouse architecture, and AI agent capabilities. It integrates Apache Kafka, Spark, and Flink to process billions of events daily with sub-100ms query latency, enabling businesses to move from raw data to intelligent insights through a low-code interface.
AgentFlow Enterprise is an AI agent development platform for building autonomous workflows on live lakehouse data. It features a visual drag-and-drop canvas for designing multi-step agentic workflows, natural language configuration, and one-click production deployment.
Dataverses provides AI-powered BI through natural language querying, automated insight generation, and no-code model training. Users can ask questions in plain English, receive automated anomaly detection and trend analysis, and deploy ML models without writing code.
Dataverses supports 50+ data sources including PostgreSQL, MongoDB, MySQL, AWS, Google Cloud, Salesforce, and message queues. Data ingestion uses Zero-ETL CDC (Change Data Capture) to automate real-time data capture without manual pipeline development.
The Dataverses Lakehouse combines data lake flexibility with data warehouse performance using Apache Iceberg. Benefits include ACID transactions, schema evolution, time travel queries, unified storage for structured and unstructured data, and optimized performance for AI/agent workloads.
Yes. Dataverses processes billions of events daily with automatic horizontal scaling. The enterprise-grade Kafka infrastructure and processing engines maintain sub-100ms query latency regardless of data volume or query load.
Dataverses offers cloud-hosted SaaS, on-premises, and hybrid deployment options. Enterprise customers receive 24/7 support, dedicated customer success managers, comprehensive API documentation, and 99.99% uptime SLA.
Organizations can deploy production-ready data systems in minutes using Dataverses' intuitive UI. The platform eliminates weeks of setup time with automated configuration, zero operational overhead, and pre-built connectors for 50+ data sources.
Discover Dataverses Resources
Stay updated with the latest insights, best practices, and technical deep-dives from our data engineering and analytics experts.
Code Smarter, Not Harder: Meet the New Notebook Code Generation on Dataverses
Apache Iceberg 1.11.0 Release: Deletion Vectors, Variant Type, and V3 Maturity
Spark Declarative Pipelines in Apache Spark 4.1: A Complete Guide
Iceberg Summit 2026: The Open Table Format That's Powering the Next Generation of Data Lakehouses
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