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AI-READY DATA PRODUCTS

From fragmented data to an AI context foundation

Create reusable, entity-centric data products that turn multi-source enterprise data into unified, governed, fresh business context for AI.

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AI-READY DATA PRODUCTS
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AI needs business context, not fragmented data

K2view turns fragmented enterprise data into AI-ready data products organized around business entities such as customers, accounts, orders, and claims.

These reusable data products create the context foundation for AI, keeping business context current and supporting governed read and write-back.

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What makes K2view data products AI-ready

Five capabilities span design-time and runtime, with AI automating much of the work to create and evolve data products.

  • 01 Data discovery & classification
  • 02 Business entity modeling
  • 03 Entity-based data integration
  • 04 Dynamic governance
  • 05 Policy-driven synchronization

01Data discovery & classification

AI-assisted discovery profiles enterprise data, classifies sensitive fields, identifies relationships, and enriches metadata with AI-generated descriptions, all managed in the data catalog.

Data discovery & classification

02Business entity modeling

AI accelerates modeling by using catalog metadata to identify business entities, suggest the root table for each entity, and bring relevant tables, fields, and cross-system relationships into the entity model.

Business entity modeling

03Entity-based data integration

The entity model defines how each table is populated for every entity instance.

Auto-generated ingestion flows query the required source data and can validate, enrich, mask, or transform it before it becomes part of the entity’s business context.

Entity-based data integration

04Dynamic governance

Access to data and permitted actions are determined dynamically for each interaction, based on the user, task, permissions, and privacy requirements.

Dynamic governance

05Policy-driven synchronization

Entity data is synchronized bi-directionally with source systems according to freshness policies defined for each use case, keeping business context current for AI.

Policy-driven synchronization

See AI-ready data products in action

See how entity-centric data products turn multi-source enterprise data into business operational context for AI.

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A reusable data product for each business entity

K2view data products are defined around business entity types such as customers, accounts, orders, and claims. Each packages the schema and reusable logic for ingesting, transforming, governing, synchronizing, and delivering multi-source enterprise data.

The same definition is applied at runtime to every instance of that entity, creating and maintaining its business context.

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k2view Semantic layer for AI-ready data

One context unit for every business entity

At runtime, each entity instance, such as an individual customer, gets its own isolated Micro-Database™, which manages its data and context. Dynamic in-memory caching enables millisecond access to entity context.

K2view synchronizes each Micro-Database with source systems according to use-case freshness policies, while supporting governed read and write-back. For unstructured data, the Micro-Database can also serve as a vector store for RAG.

The result is business-fresh context that AI can reason over and safely act on.

 

One context unit for every business entity
Pelephone case study

Pelephone powers GenAI customer service with trusted customer context

"For a GenAI-powered chatbot to be smart and effective, a GenAI-ready data infrastructure is required. That’s where K2view enters the picture."

Maya Bachar Gilad, Chief Information Officer, Pelephone
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"For a GenAI-powered chatbot to be smart and effective, a GenAI-ready data infrastructure is required. That’s where K2view enters the picture."

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Cellcom case study

Cellcom transforms customer service with AI-ready customer data

"K2view allows us to combine GenAI and AI-ready customer data to transform customer service, and deliver real business value faster than ever."

Victor Malka, Chief Information Officer, Cellcom
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"K2view allows us to combine GenAI and AI-ready customer data to transform customer service, and deliver real business value faster than ever."

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Gartner Peer Review

"K2view has a unique approach of integrating enterprise data with the LLM's advantage"

Office of the CIO manager, Telecom
Company size: 50M - 250M USD
Frame 91213
Office of the CIO manager, Telecom

Business operational context, ready for AI

AI context must be complete by entity

Complete by entity

Each entity’s context unifies relevant data, relationships, and business semantics across enterprise sources.

AI context must be trusted

Trusted

Entity context is built from validated, cleansed, and resolved data, with quality policies enforced during ingestion.

AI context must be accessible in milliseconds

Read/write access

Entity context is available in milliseconds via APIs and MCP, with RAG retrieval and governed write-back to source systems.

AI context must be governed

Governed

Entity context and actions are governed dynamically per interaction based on user, task, permissions, and policy.

Business-fresh context for AI

Business-fresh

Entity context is synchronized with source systems according to each use case’s freshness requirements.

K2VIEW RESEARCH

K2VIEW RESEARCH

Enterprise AI needs an AI context platform

Our survey of 300 organizations explores why fragmented enterprise data remains a barrier to production AI, and how companies are evolving their data foundations to support AI context platforms with trusted, current business context.

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