One integrated platform. Everything your data team needs.
Every module runs on the same Apache Spark + Kubernetes foundation. Same catalog, same RBAC, same operational surface, so switching modules isn't switching contexts.
From cloud infrastructure to BI. One stack.
Layered on a battle-tested compute foundation, Spark on Kubernetes, with auto-scaling, multi-cluster, and cloud-agnostic deployment.
Business Intelligence
Intelligence
Delivery
Processing
Ingestion
Governance
Sources
↑ Apache Spark · Kubernetes auto-scaling · Multi-cluster · Cloud-agnostic (AWS · Azure · GCP · Private) ↑
Grouped by what they do for you.
Each module is fully production-grade on its own. They share a data model, a security model, and a catalog, so teams stop paying the integration tax between them.
Intelligence
Operations
Delivery
Governance
Agents across platform.
A growing library of agents ships with the platform, regardless of which modules you turn on. No separate contract, no separate model to manage.
Talk to Your Data
Plain-English queries over SQL, NoSQL, S3, Cassandra, and APIs.
ETL/ELT Designer
Describe the requirement, and the agent ships a deployment-ready pipeline.
Spark Summarizer
Turns verbose Spark logs into "what ran, failed, was slow, fix this."
ProcBot Designer
Describe a process, and the agent generates the working script in bash, Python, Terraform, or Ansible.
Sherlock
Autonomous agents help with not only problem discovery but throughout the process from problem detection to auto-remediation and closure.
DataOps AI
Ask about pipeline health and SLAs; answers come from live telemetry.
AI Governance & Intelligence
AI agents continuously enrich metadata, classify sensitive data, monitor compliance, and generate governance insights across enterprise data assets.
Data Exploration AI
Describe the requirements in natural language, and the agent generates the transformation code behind the scenes to produce the output.
Connects to where your data already lives.
Two thousand plus connectors across six categories, delivered through the Advance ETL engine. Drag-and-drop by default; custom code when the source demands it.
Databases & warehouses
- PostgreSQL
- MySQL
- Oracle
- SQL Server
- Snowflake
- BigQuery
- Redshift
- MongoDB
- Cassandra
Cloud storage
- AWS S3
- Azure Blob
- GCS
- Azure Data Lake
- HDFS
- MinIO
Streaming & messaging
- Apache Kafka
- AWS Kinesis
- Azure Event Hubs
- RabbitMQ
- Webhooks
- REST APIs
SaaS & applications
- Salesforce
- SAP
- ServiceNow
- Workday
- HubSpot
- Zendesk
- Jira
- + 280 more
BI & reporting
- Power BI
- Tableau
- Looker
- Excel
- SFTP export
- Email delivery
File formats
- CSV / JSON / XML
- Parquet
- Avro
- ORC
- FTP / SFTP

See it running on your stack.
Thirty-minute walkthrough. Your data, your connectors, real pipelines. No slideware.