Blog - K2view

K2view named a Visionary in 2026 Gartner Magic Quadrant

Written by Oren Ezra | November 3, 2026

We’re thrilled to share that we’ve been named a Visionary in the 2026 Gartner® Magic Quadrant™ for Data Integration Tools. This is our fourth consecutive year in the Visionaries quadrant.

We’re proud of the work behind that recognition. Over the past year, we’ve expanded our Data Product Platform to help enterprises create data products from business intent and deliver governed business context to AI agents. Those investments build on our experience supporting demanding operational data workloads.

The data foundation behind enterprise AI

Consider an AI agent recommending a mobile plan. It needs current usage, the customer’s existing commitments, and the rules that determine eligibility. If the customer accepts, it needs permission to submit the change to the underlying systems.

Our focus is on making that entire interaction possible.

We organize multi-source data and knowledge around business entitiesA business entity is something an organization tracks and manages, such as a customer, account, product, order, or claim. K2view unifies and manages the data for each individual entity, such as a specific customer, in its own Micro-Database™.Explore K2view Micro-Database technology, managing each entity instance in its own Micro-Database™A Micro-Database™ is K2view’s dedicated data store for a single business entity instance, such as a specific customer, account, or order. It unifies that entity’s data and relationships across source systems, stays synchronized with those systems, and provides fast, independently governed access.Explore K2view Micro-Database technology. Our AI Context Layer delivers the specific business context an agent needs for its task, with runtime governance over access and actions. Evaluation and observability help teams assess outcomes against the context the agent actually received.

Three strengths in this year’s Magic Quadrant

The report identifies three strengths for K2view that span our operational foundation and AI capabilities:

  • Built for operational scale. Our entity-centric Micro-Database architecture supports parallel, in-memory processing for high throughput and low latency. Teams can switch between batch, replication, streaming, and virtualization as workload requirements change.
  • Data product lifecycle support. We help teams design, integrate, govern, and operate reusable data products. Separating product definitions from runtime instances supports schema evolution and CI/CD as those products change.
  • Strong AI vision. K2assistant enables natural language interactions, while K2skills captures repeatable engineering practices as reusable skills for configuring data products and AI agents. We also support AI context delivery, runtime governance, and evaluation and observability of agent performance in production.

AI enablement and advanced transformation

In the accompanying 2026 Critical Capabilities for Data Integration Tools report, our highest-rated capabilities were AI Enablement and Advanced Data Transformation.

These are closely related in our platform. Preparing enterprise data for AI often requires complex transformations across different systems and formats. Our Broadway orchestration technology provides more than 200 out-of-the-box data transformations, including transformation pushdown to Snowflake and Databricks, in-memory processing for stateful logic, and LLM-based image and document processing.

Teams can build on that same data product foundation for AI context management, Customer 360, test data management, and synthetic data generation.

Thank you to the people behind the work

We’re grateful to our customers for trusting us with their critical data workloads and pushing us to solve difficult problems. And we’re proud of our team and partners for the expertise and commitment they bring to that work.

Four consecutive years as a Visionary is a milestone we’re excited to celebrate. We’ll keep building on the operational foundation our customers depend on as we expand what they can accomplish with enterprise AI.