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K2view Recognized as Visionary for Third Consecutive Year in 2025 Gartner® Magic Quadrant™ for Data Integration Tools

K2view secures $15M to fuel the next generation of Agentic AI, powered by AI-ready data

Rocket Software and K2view partner to accelerate mainframe modernization
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K2view is a Visionary in the 2025 Gartner MQ 🎉
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K2view Recognized as Visionary for Third Consecutive Year in 2025 Gartner® Magic Quadrant™ for Data Integration Tools
K2view secures $15M to fuel the next generation of Agentic AI, powered by AI-ready data
Rocket Software and K2view partner to accelerate mainframe modernization

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K2view climbs higher as a Visionary in the Gartner Magic Quadrant for Data Integration Tools 2025

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K2view climbs higher as a Visionary in the Gartner Magic Quadrant for Data Integration Tools 2025

K2view climbs higher as a Visionary in the Gartner Magic Quadrant for Data Integration Tools 2025

Gartner names K2view a Visionary in its Magic Quadrant for Data Integration Tools for the 3rd year in a row and rates us higher in our ability to execute.

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Iris Zarecki

Product Marketing Director

Iris Zarecki is a B2B tech marketing expert with over 30 years of experience, specializing in Generative AI (GenAI), AI/ML, data integration, and external data. With a rich background in promoting enterprise technology across global markets, she has held key marketing roles in both startups and large corporations. Currently Director of Product Marketing at K2view, Iris helps enterprises harness their data to drive innovation, efficiency, and AI readiness.

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K2view
AI Agents
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GenAI isn’t broken. Your data architecture is.

May 3, 2026

GenAI isn’t broken. Your data architecture is.

Most GenAI pilots look successful until they face real data, real customers, and real operational constraints. Here is why they fail at scale. The GenAI theory...

AI Data Readiness

Why traditional data architectures fail when GenAI goes into production

February 26, 2026

Why traditional data architectures fail when GenAI goes into production

Why operational GenAI changes data architecture requirements, and why architecture, not LLMs, determines GenAI trust, latency, cost, and adoption. Operational...

AI Data Readiness

Conversational AI market: Transforming business at an explosive rate

November 9, 2025

Conversational AI market: Transforming business at an explosive rate

The conversational AI market is driving enterprise transformation with 23.7% CAGR growth, reaching $41.39 billion by 2030 according to Grand View Research.

Conversational AI

Conversational AI in banking: Enhancing the user experience with smart automation

November 9, 2025

Conversational AI in banking: Enhancing the user experience with smart automation

Conversational AI in banking revolutionizes customer service with 24/7 support, personalized interactions, and secure transactions via bank savvy chatbots.

Conversational AI

An app-centric MCP does NOT know your customer

September 28, 2025

An app-centric MCP does NOT know your customer

Problem: When the Model Context Protocol (MCP) is designed for a single platform (SAP, Salesforce, SQL Server), it loses business focus. Solution: K2view.

Model Context Protocol (MCP)

Conversational AI vs generative AI: Understanding the key differences for enterprise success

October 19, 2025

Conversational AI vs generative AI: Understanding the key differences for enterprise success

Comparing conversational AI and generative AI highlights their respective purposes, applications, training styles, and customer service enhancement goals.

Conversational AI

Agent assist: Empowering human customer services reps to respond smarter and quicker

May 5, 2026

Agent assist: Empowering human customer services reps to respond smarter and quicker

Agent assist is AI tech that provides real-time guidance, contextual insights, and business recommendations to customer service agents during interactions.

Conversational AI AI Agents

Conversational AI for customer service: Transforming support in the digital age

October 16, 2025

Conversational AI for customer service: Transforming support in the digital age

Conversational AI for customer service is AI technology that automates customer support, resolves issues, and enhances the user experience in real time.

Conversational AI

Conversational AI chatbot vs assistants: Understanding the differences

October 20, 2025

Conversational AI chatbot vs assistants: Understanding the differences

While a conversational AI chatbot is designed for simple conversations, virtual assistants have a broader feature set enabling more complex interactions.

Conversational AI

Conversational AI Chatbot accuracy: Why it matters and how to achieve it

October 16, 2025

Conversational AI Chatbot accuracy: Why it matters and how to achieve it

Conversational AI chatbot accuracy is the degree to which a chatbot can interpret user queries and provide correct, relevant, and context-aware responses.

Conversational AI

Conversational AI in healthcare: Just what the doctor ordered

November 9, 2025

Conversational AI in healthcare: Just what the doctor ordered

Conversational AI in healthcare is a technology that uses AI to allow patients, providers, and staff to communicate through chatbots or virtual assistants.

Conversational AI

Conversational AI platform vendors abound but which is right for you?

October 16, 2025

Conversational AI platform vendors abound but which is right for you?

A conversational AI platform is a solution enabling text or voice interactions between people and machines often using LLMs augmented with enterprise data. Who...

Conversational AI

MCP enterprise deployments combine company data with agentic RAG

September 28, 2025

MCP enterprise deployments combine company data with agentic RAG

MCP for the enterprise is a standardized protocol that grounds LLMs with real-time company data and uses agentic RAG to generate more contextual responses.

Model Context Protocol (MCP)

Salesforce MCP: Connecting AI agents to enterprise data

October 19, 2025

Salesforce MCP: Connecting AI agents to enterprise data

Model Context Protocol (MCP) enables AI agents to leverage Salesforce and other enterprise systems in real time, to boost GenAI response accuracy and data...

Model Context Protocol (MCP)

MCP SQL server: Connecting LLMs to trusted enterprise data

April 28, 2026

MCP SQL server: Connecting LLMs to trusted enterprise data

MCP SQL server lets AI tools securely access real-time SQL server data and context, enhancing AI insights, accuracy, and data governance across systems.

Model Context Protocol (MCP)

SAP MCP: Unlocking SAP data access for AI agents

April 29, 2026

SAP MCP: Unlocking SAP data access for AI agents

MCP for SAP enables AI to securely access real-time SAP data and context, improving agentic AI accuracy and data governance across SAP landscapes.

Model Context Protocol (MCP)

Awesome MCP servers: Directory of the top 15 for 2026

April 24, 2026

Awesome MCP servers: Directory of the top 15 for 2026

This comprehensive MCP directory for 2026 rates 15 awesome MCP servers in terms of how they access AI tools, inject enterprise data, enable RAG, and more.

Model Context Protocol (MCP)

What is Model Context Protocol?

April 30, 2025

What is Model Context Protocol?

Model Context Protocol (MCP) is a standard for connecting LLMs to enterprise data sources in real time, to ensure compliant and complete GenAI responses.

Model Context Protocol (MCP)

MCP Gartner insights for 2025

November 23, 2025

MCP Gartner insights for 2025

Industry analyst firm Gartner points out that while the MCP protocol simplifies how AI apps, agents, and data sources connect, it also introduces security and...

Model Context Protocol (MCP)

What are AI Agents?

April 14, 2025

What are AI Agents?

AI agents are autonomous systems designed to analyze data, make decisions, and take actions to complete tasks, solve problems, or assist human users.

RAG

What is Agentic AI?

April 14, 2025

What is Agentic AI?

Agentic AI is an agent-based AI system that employs chain-of-thought reasoning and iterative planning to autonomously complete complex, multi-step tasks.

RAG

What is Table Augmented Generation (TAG)?

April 14, 2025

What is Table Augmented Generation (TAG)?

Table Augmented Generation (TAG) is a framework that improves the accuracy of GenAI responses by injecting structured enterprise data into the LLM prompts.

RAG

Conversational AI chatbots: Benefits, use cases, and challenges

October 16, 2025

Conversational AI chatbots: Benefits, use cases, and challenges

A conversational AI chatbot uses artificial intelligence to simulate conversations between people via natural language processing and contextual awareness.

Conversational AI

What is conversational AI?

April 27, 2025

What is conversational AI?

Conversational AI is a technology that enables computers to understand, process, and respond to human language in a natural and contextually relevant way.

Conversational AI

AI customer experience = Better interactions between sellers and buyers

October 16, 2025

AI customer experience = Better interactions between sellers and buyers

Companies are leveraging AI to make customer journeys smoother, more efficient, and more satisfying – by automating support and personalizing interactions.

Conversational AI

Customer service chatbots are transforming customer care

October 16, 2025

Customer service chatbots are transforming customer care

Customer service chatbots are applications designed to support customers more quickly, efficiently, and comprehensively, while reducing operational costs.

Conversational AI

Unleashing the power of agentic AI: K2view launches Data Agent Builder

May 5, 2026

Unleashing the power of agentic AI: K2view launches Data Agent Builder

Unlock the power of no-code agentic AI to build intelligent, data-driven agents effortlessly. Leverage enterprise data for smarter, more efficient AI apps.

K2view AI Data Readiness

Snowflake RAG: When Snowflake meets retrieval-augmented generation

May 5, 2026

Snowflake RAG: When Snowflake meets retrieval-augmented generation

Snowflake RAG, proficient in analytical GenAI with response times measured in minutes, can now support real-time operational GenAI, thanks to K2view.

AI Data Readiness

AI virtual assistants streamline tasks and increase efficiency

October 16, 2025

AI virtual assistants streamline tasks and increase efficiency

AI virtual assistants are software programs that use AI to perform tasks on demand. Companies use them to enhance customer service and boost productivity.

Conversational AI

AI customer service: Revolutionizing support with AI chatbots

October 16, 2025

AI customer service: Revolutionizing support with AI chatbots

AI customer service transforms support by automating tasks, personalizing interactions, resolving issues instantly, and working 24/7 with no down time.

Conversational AI

LLM single action agent solutions target lone task completion

May 5, 2026

LLM single action agent solutions target lone task completion

An LLM single action agent is an AI system designed to respond to a specific query more effectively by leveraging the power of your large language model.

AI Data Readiness

LLM graph database: Better data queries, insights, and understanding

May 5, 2026

LLM graph database: Better data queries, insights, and understanding

LLM graph databases merge LLMs with graph DBs to enable natural language querying, enriched data insights, and deeper understanding of data relationships.

AI Data Readiness

LLM SQL agents: Querying data in plain English

May 5, 2026

LLM SQL agents: Querying data in plain English

An LLM SQL agent accurately converts text queries into SQL commands to increase productivity and enable users to access enterprise data easily.

AI Data Readiness

ReACT agent LLM: Making GenAI react quickly and decisively

May 5, 2026

ReACT agent LLM: Making GenAI react quickly and decisively

A ReACT agent LLM is an AI model combining reasoning and actions to enable dynamic problem-solving, by thinking step-by-step and working with other tools.

AI Data Readiness

Top AI RAG tools for 2026

May 5, 2026

Top AI RAG tools for 2026

AI RAG tools enhance LLM outputs. Here’s a comparison of the 6 leaders in the field: K2view, Haystack, Langchain, LlamaIndex, RAGatouille, and EmbedChain.

AI Data Readiness

LLM powered autonomous agents drive GenAI productivity and efficiency

June 3, 2025

LLM powered autonomous agents drive GenAI productivity and efficiency

LLM-powered autonomous agents are independent systems that leverage large language models to make decisions and perform tasks without a human in the loop.

RAG

RAG vs prompt engineering: Getting the best of both worlds

June 3, 2025

RAG vs prompt engineering: Getting the best of both worlds

For more accurate LLM responses, RAG integrates enterprise data into LLMs while prompt engineering tailors instructions. Learn how to get the best of both.

RAG

Multi agent LLM systems: GenAI special forces

June 3, 2025

Multi agent LLM systems: GenAI special forces

A multi agent LLM system is comprised of multiple intelligent agents, powered by a large language model, that work together to accomplish complex tasks.

RAG

LLM prompt engineering: The first step in realizing the potential of GenAI

May 27, 2025

LLM prompt engineering: The first step in realizing the potential of GenAI

LLM prompt engineering is a methodology designed to improve the responses generated by your large language model using retrieval and generative components.

RAG

Generative AI use cases in customer service

October 16, 2025

Generative AI use cases in customer service

More and more enterprises are turning to generative AI use cases in customer service to pilot their GenAI initiatives. Discover why in our recent survey.

Conversational AI

RAG structured data: Leveraging enterprise data for GenAI

May 27, 2025

RAG structured data: Leveraging enterprise data for GenAI

RAG structured data is structured data retrieved from your enterprise systems and augmented into your LLM for more accurate and context-aware responses.

RAG

Generative AI adoption is still in its infancy

May 27, 2025

Generative AI adoption is still in its infancy

Generative AI adoption is the process by which organizations experiment with, and pilot, GenAI initiatives. Here are highlights from our recent survey.

RAG

What is best practice when using generative AI? Insights from Gartner

May 27, 2025

What is best practice when using generative AI? Insights from Gartner

Generative AI can boost productivity and innovation, but its adoption can be challenging. Learn about GenAI best practices from Gartner analysts.

RAG

AI data privacy: Protecting financial information in the AI era

June 2, 2026

AI data privacy: Protecting financial information in the AI era

AI data privacy is the set of security measures taken to protect the sensitive data collected, stored, and processed by AI apps, frameworks, and models.

RAG

LLM Agent Architecture Enhances GenAI Task Management

April 21, 2025

LLM Agent Architecture Enhances GenAI Task Management

An LLM agent architecture is a framework combining a large language model with other components to enable better task execution and real-world interaction.

RAG

Generative AI Data Augmentation: An IDC Research Snapshot

April 21, 2025

Generative AI Data Augmentation: An IDC Research Snapshot

GenAI data augmentation enhances AI models with structured, unstructured, and semi-structured data from enterprise systems for improved query responses.

RAG

LLM agent framework: Quietly completing complex AI tasks

May 27, 2025

LLM agent framework: Quietly completing complex AI tasks

An LLM agent framework is a software platform that creates and manages LLM-based agents that autonomously interact with their environment to fulfill tasks.

RAG

Prompt engineering vs fine-tuning: Understanding the pros and cons

November 23, 2025

Prompt engineering vs fine-tuning: Understanding the pros and cons

Prompt engineering is a process that improves LLM responses by well crafted inputs. Fine-tuning trains a model on domain-specific data. Which to use when?

RAG

LLM function calling goes way beyond text generation

May 27, 2025

LLM function calling goes way beyond text generation

LLM function calling is the ability of a large language model to perform actions besides generating text by invoking APIs to interface with external tools.

RAG

RAG architecture + LLM agent = Better responses

May 27, 2025

RAG architecture + LLM agent = Better responses

RAG architectures powered by LLM agents retrieve relevant data from internal and external sources to generate more accurate and contextual responses.

RAG

What are LLM agents?

October 7, 2024

What are LLM agents?

LLM agents are AI tools that leverage Large Language Models (LLMs) to perform tasks, make decisions, and interact with users or other systems autonomously.

RAG

LLM guardrails guide AI toward safe, reliable outputs

May 27, 2025

LLM guardrails guide AI toward safe, reliable outputs

LLM guardrails are agents that ensure that your model generates safe, accurate, and ethical responses by monitoring and controlling its inputs and outputs.

RAG

Generative AI use cases: Top 10 for enterprises in 2025

May 27, 2025

Generative AI use cases: Top 10 for enterprises in 2025

Generative AI use cases are AI-powered workloads designed to create content, enhance creativity, automate tasks, and personalize user experiences.

RAG

LLM vector database: Why it’s not enough for RAG

May 27, 2025

LLM vector database: Why it’s not enough for RAG

LLM vector databases store vector embeddings for similarity search, but lack the structural data integration and contextual reasoning needed for RAG.

RAG

Prompt engineering techniques: Top 6 for 2026

April 28, 2026

Prompt engineering techniques: Top 6 for 2026

Prompt engineering techniques – such as zero-shot, few-shot, chain-of-thought, meta, self-consistency, and role – enhance the accuracy of LLM responses.

RAG

LLM text-to-SQL solutions: Top challenges and tips

April 28, 2026

LLM text-to-SQL solutions: Top challenges and tips

LLM-based text-to-SQL is the process of using Large Language Models (LLMs) to automatically convert natural language questions into SQL database queries.

RAG

AI prompt engineering: The art of AI instruction

May 27, 2025

AI prompt engineering: The art of AI instruction

AI prompt engineering is the process of giving a Large Language Model (LLM) effective instructions for generating accurate responses to user queries.

RAG

Grounding data is like doing a reality check on your LLM

May 27, 2025

Grounding data is like doing a reality check on your LLM

Grounding data is the process of exposing your Large Language Model (LLM) to real-world data to ensure it responds to queries more accurately and reliably.

RAG

Chain-of-thought reasoning supercharges enterprise LLMs

May 27, 2025

Chain-of-thought reasoning supercharges enterprise LLMs

Chain-of-thought reasoning is the process of breaking down complex tasks into simpler steps. Applying it to LLM prompts results in more accurate responses.

RAG

RAG vs fine-tuning vs prompt engineering: And the winner is...

May 27, 2025

RAG vs fine-tuning vs prompt engineering: And the winner is...

RAG, fine-tuning, and prompt engineering are all techniques designed to enhance LLM response clarity, context, and compliance. Which works best for you?

RAG

AI database schema generator: What is it? Why is it critical for LLMs?

May 27, 2025

AI database schema generator: What is it? Why is it critical for LLMs?

An AI database schema generator is a tool using AI to automate the creation and management of database schemas. Schema-aware LLMs respond more accurately.

RAG

RAG prompt engineering makes LLMs super smart

July 8, 2025

RAG prompt engineering makes LLMs super smart

Retrieval-Augmented Generation (RAG) prompt engineering is a generative AI technique that enhances the responses generated by Large Language Models (LLMs).

RAG

Grounding AI reduces hallucinations and increases response accuracy

May 27, 2025

Grounding AI reduces hallucinations and increases response accuracy

Grounding AI is the process of connecting large language models to real-world data to prevent hallucinations and ensure more reliable and relevant outputs.

RAG

Chain-of-thought prompting 101

May 27, 2025

Chain-of-thought prompting 101

Chain-of-thought prompting is a technique that trains GenAI models to use step-by-step reasoning to handle complex tasks with greater accuracy and agility.

RAG

Data readiness can make or break your GenAI projects

November 12, 2025

Data readiness can make or break your GenAI projects

AI data readiness is the process of ensuring data is fit, trustworthy, and optimized for use in AI models. Jean-Luc Chatelain explains how it affects...

RAG

Generative AI hallucinations: When GenAI is more artificial than intelligent

May 27, 2025

Generative AI hallucinations: When GenAI is more artificial than intelligent

Generative AI hallucinations are incorrect or nonsensical GenAI outputs, resulting from flawed data or misinterpretations of data patterns during training.

RAG

The GenAI data gap: Is your enterprise ready for generative AI?

October 28, 2025

The GenAI data gap: Is your enterprise ready for generative AI?

What’s keeping you from realizing the full potential of generative AI? The GenAI data gap, of course! It's high time your enterprise had AI-ready data.

RAG

RAG architecture: The generative AI enabler

May 27, 2025

RAG architecture: The generative AI enabler

RAG architecture enables real-time retrieval and integration of publicly available and privately held company data that enhances LLM prompts and responses.

RAG

LLM hallucination risks and prevention

June 15, 2025

LLM hallucination risks and prevention

An LLM hallucination refers to an output generated by a large language model that’s inconsistent with real-world facts or user inputs. RAG helps avoid them.

RAG

What is an AI Hallucination?

May 5, 2024

What is an AI Hallucination?

An AI hallucination is an AI-generated output that’s factually incorrect, nonsensical, or inconsistent, due to bad training data or misidentified patterns.

RAG

What is grounding and hallucinations in AI?

April 29, 2026

What is grounding and hallucinations in AI?

Grounding is a method designed to reduce AI hallucinations (false or misleading info made up by GenAI apps) by anchoring LLM responses in enterprise data.

RAG

RAG hallucination: What is it and how to avoid it

April 29, 2026

RAG hallucination: What is it and how to avoid it

Although regular RAG grounds LLMs with unstructured data from internal sources, hallucinations still occur. Add structured data to the mix to reduce them.

RAG

RAG conversational AI – Making your GenAI apps more effective with RAG

October 20, 2025

RAG conversational AI – Making your GenAI apps more effective with RAG

Supercharge conversational AI with Retrieval-Augmented Generation (RAG) for responses that are as complete, compliant, and current as your enterprise data.

Conversational AI

RAG chatbot: What’s it all a bot?

April 29, 2026

RAG chatbot: What’s it all a bot?

RAG chatbots are generative AI apps that combine retrieval and generation models to enable more accurate and relevant responses than traditional chatbots.

RAG

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