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AI-Ready Data

Fuel GenAI with trusted, AI-ready data

With real-time data and built-in trust, GenAI always gets it right.

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The hard truth
about data for GenAI

Grounding GenAI in enterprise truth requires more than raw data. It demands AI-ready data that is fresh, integrated, and contextualized. K2view delivers governed data in real time, enabling accurate, personalized GenAI responses at conversational speed.

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How K2view delivers AI-ready data

Five core capabilities that make data truly AI-ready

Live, harmonized, and secure data grounds GenAI, ensuring every response is accurate and trustworthy.

 

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Real-Time Data Retrieval

GenAI applications don’t have minutes to wait — they need answers in milliseconds. Traditional approaches that query data warehouses or lakes may be acceptable for analytics, but they’re far too slow for conversational use cases like customer service chatbots or virtual assistants.

K2view uses text-to-SQL and schema awareness to generate the right query for every user question and instantly retrieve the answer. The result is accurate, personalized responses at conversational speed.

Live Data Integration

Every GenAI response depends on data that’s accessible live, without compromise. Other approaches either overload operational systems by querying massive datasets or rely on analytical stores where data is stale.

K2view avoids both pitfalls. By retrieving only the data for a single business entity, the platform eliminates system load while ensuring freshness. With continuous entity resolution and flexible ingestion (CDC, streaming, messaging, or APIs), every entity’s dataset is always-fresh and ready for GenAI.

Semantic Enrichment

GenAI needs more than raw data — it needs to understand meaning. K2view enriches enterprise data with semantic meaning, relationships, lineage, and business context. This enables LLMs to generate accurate SQL queries over complex schemas.

The same semantic layer ensures that once data is retrieved, it’s interpreted in the correct business context. GenAI responses are therefore precise, relevant, and trustworthy.

In-Flight Data Governance

AI can only be trusted if both the data it uses and the responses it generates are high-quality, compliant, and auditable. K2view enforces governance in-flight by applying fine-grained access controls, enforcing data quality policies, and maintaining full traceability of usage and outputs.

Every response is accurate, consistent, and compliant — building trust in every interaction.

Entity-Level Isolation

Every GenAI interaction should be confined within strict boundaries. With K2view, each interaction is scoped to the data of a single Micro-Database, representing one customer, account, or employee.

These built-in guardrails prevent responses from extending beyond the boundaries of that entity’s data. A customer using a chatbot cannot query details about another customer, and an employee using an HR assistant cannot access information about a colleague. By isolating each entity, K2view ensures GenAI responses remain private, compliant, and secure.

Semantic layer for AI-ready data

K2view’s patented semantic layer delivers the five attributes of AI-ready data: instant retrieval, live freshness, semantic context, in-flight governance, and strict isolation. It achieves this by organizing fragmented enterprise information into millions of Micro-Databases™, each dedicated to a single business entity.

Powered by dynamic caching, cleansing, and anonymization, Micro-Database technology harmonizes structured and unstructured data across sources without straining operational systems.

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Semantic data layer for AI-ready data

Retrieval layer for AI-ready data

K2view’s semantic data layer unifies access to structured and unstructured enterprise data, making it instantly consumable by GenAI apps. At the core, each Micro-Database stores structured data for a single business entity and vectorizes its associated unstructured content—such as documents, logs, or emails—so both can be retrieved with precision.

Through the Model Context Protocol (MCP), K2view provides an MCP data integration server that orchestrates each request into a contextual response, exposing governed, entity-based data products as live APIs.  

In parallel, K2view natively supports Retrieval-Augmented Generation (RAG) by serving as the RAG engine for both structured and unstructured data. This enables GenAI apps to generate responses that are fluent, contextually rich, and factually correct.

Retrieval Layer for AI-Ready Data: MCP and RAG
Pelephone case study

Pelephone elevates customer experience with K2view GenAI Data Fusion

"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 combines GenAI and customer data to improve customer service

"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
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Office of the CIO manager, Telecom
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Your data, always AI-ready

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Accessible in ms

Accessible in milliseconds, by authorized data consumers, to ensure conversational latency response.

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In sync

Data is synced from source systems based on your policies, ensuring it is always fresh and up-to-date. This allows your GenAI applications to deliver trusted responses.

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Secured

The data is secured with its own, unique encryption key, and isolated at the business entity level, ensuring that each user can access only their own data.

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Compliant

LLM access to sensitive data must be controlled. Our technology ensures users can only access their own data, preventing private data from leaking into LLMs.

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Cached

The data can be cached into memory, persisted, or virtualized, for optimal performance and minimal overload.

Just 2% of US and UK businesses are ready for production GenAI

Our 2024 Enterprise Data Readiness for GenAI survey reveals the top challenges enterprises face as they work toward GenAI deployments.

The most significant GenAI roadblocks lie in the data infrastructure, particularly in the areas of data accessibility and latency, data privacy, and security.

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