Tackle data quality and speed up your integration builds using your current stack. Easily implemented with top iPAAS providers and your data pipelines, accelerated with AI.

Simplify complexity and accelerate integrations

Support a composable app strategy and deliver on automation and AI capabilities

Extend your legacy iPAAS infrastructure

Decompose your data and service monoliths, and adopt new tech faster and cheaper.

Unify and distribute data at scale

Match, merge, enrich data in one single place Simplify integration patterns and reduce constant sync requirements

Improve data quality continuously

Deliver on priority projects with less resources while increasing data usability for the entire organization

Delivering AI for the Enterprise

Pivotly AI Capabilities

Pivotly delivers a suite of AI-powered tools that accelerate development, simplify integration, and enhance data management.

  • Automated Data Modeling: Automatically structures raw data into domains, reducing developer workload.
  • Intelligent Data Mapping: Creates dynamic “liquid maps” for seamless data transformation.
  • AI-Generated Apps: Builds applications for data visualization and troubleshooting.
  • Automated Egress Mapping: Automatically formats data for external use, reducing manual efforts.
  • Natural Language Queries: Enables easy access to insights using everyday language

Pivotly Enabling AI Adoption

Pivotly supports enterprises in adopting AI by simplifying data access, scaling integrations, and enhancing intelligence.

  • AI-Enhanced Productivity: Reduces development complexity and boosts efficiency.
  • AI-Ready Microservices: Seamlessly integrates AI with enterprise data for business automation.
  • Scalability for AI Agents: Allows multiple AI agents to interact with shared data, accelerating deployment.
  • Rich Metadata for Smarter AI: Provides data quality rules and complete datasets for better AI decision-making.
  • Future-Proof AI Solutions: Easily integrates new AI technologies to stay ahead in innovation.

Deliver on your immediate project needs while making continuous progress towards your data goals.

For Data
Engineers

Data Modeling and governance with integrations populating shared data domains in real time.

  • Simple integration with major ETLs, Snowflake and Databricks
  • Benefit from a data hub that improves usability over time
  • Move realtime reporting out of applications and into the reporting platform.

For Integration Engineers

Create reusable data services for all future integrations, to deliver on the near term and long term business objectives

  • Massive acceleration of new tech adoption
  • Keep systems loosely coupled for maximum agility
  • Simplify complexity overall
  • Be ready for new AI projects with little ramp
Our Insights

Best Practices for Effective Data Integration Strategies

What Is a Unified Data Hub?

Data silos, fragmentation, and vendor lock-in have become significant obstacles for modern organizations seeking agility, innovation, and efficiency. Traditional data management strategies—whether relying on integration APIs or monolithic platforms—often lead to cumbersome systems that slow…

Read More

Overcoming Integration Complexity in Modular Architectures with a Unified Data Hub

Making Data Application Agnostic, Interoperable, and Usable in Modern Applications Explore the importance of having application-agnostic data that can still serve as a reliable source of truth for organizations. By adopting a unified approach to…

Download Now