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K2view Shines as Visionary in 2024 Gartner Magic Quadrant for Data Integration Tools
K2view Finds that Just 2% of U.S. and UK Businesses are Ready for GenAI Deployment
K2view Launches New Synthetic Data Management Solution
K2view a Leader in the 2023 SPARK Matrix for Data Masking Tools

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

K2VIEW BLOG

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

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

K2view lands $15M to scale its AI-ready Data Product Platform—powering agentic AI with real-time, trusted data. Backed by Trinity Capital.

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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

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

March 3, 2025

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 RAG

Snowflake RAG: When Snowflake meets retrieval-augmented generation

February 25, 2025

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.

RAG

LLM single action agent solutions target lone task completion

December 29, 2024

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.

RAG

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

December 27, 2024

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.

RAG

LLM SQL agents: Querying data in plain English

December 22, 2024

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.

RAG

ReACT agent LLM: Making GenAI react quickly and decisively

December 16, 2024

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.

RAG

Top AI RAG tools for 2025

December 10, 2024

Top AI RAG tools for 2025

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

RAG

LLM powered autonomous agents drive GenAI productivity and efficiency

December 9, 2024

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

December 8, 2024

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

November 29, 2024

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

November 27, 2024

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

RAG structured data: Leveraging enterprise data for GenAI

November 22, 2024

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

November 20, 2024

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

November 18, 2024

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

November 14, 2024

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

November 10, 2024

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

November 4, 2024

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

October 31, 2024

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

October 29, 2024

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

October 27, 2024

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

October 20, 2024

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

AI data governance enforces privacy and quality

October 14, 2024

AI data governance enforces privacy and quality

AI implementations bring data governance into sharp focus, because grounding LLMs with secure, trusted data is the only way to ensure accurate 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

September 25, 2024

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

September 17, 2024

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

September 16, 2024

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

September 11, 2024

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

September 11, 2024

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

September 5, 2024

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

August 27, 2024

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

August 26, 2024

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

Enterprise LLM: The challenges and benefits of generative AI via RAG

August 22, 2024

Enterprise LLM: The challenges and benefits of generative AI via RAG

Enterprise Large Language Models (LLMs) using Retrieval-Augmented Generation (RAG) enhance the accuracy and context of their responses with generative AI.

RAG

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

August 8, 2024

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

Enterprise RAG: Beware of connecting LLMs directly to data sources

August 8, 2024

Enterprise RAG: Beware of connecting LLMs directly to data sources

When deploying enterprise RAG, you may want to give your LLM’s agents and functions direct access your operational systems. But that’s not a great idea.

RAG

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

August 6, 2024

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

August 5, 2024

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

Data quality for AI: Through the looking glass

July 31, 2024

Data quality for AI: Through the looking glass

The concentration on generative AI puts data quality into sharp focus. Grounding LLMs with trusted private data and knowledge is more essential than ever.

RAG

RAG for structured data: The pitfalls of data lakes

July 10, 2024

RAG for structured data: The pitfalls of data lakes

Are data lakes and/or warehouses the best platforms for integrating structured data into retrieval-augmented generation architectures? Let’s find out.

RAG

Grounding AI reduces hallucinations and increases response accuracy

July 9, 2024

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

June 25, 2024

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

June 16, 2024

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

June 10, 2024

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?

May 27, 2024

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 20, 2024

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

May 12, 2024

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

AI personalization: It’s all about you!

May 7, 2024

AI personalization: It’s all about you!

AI personalization combines Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) to create personalized and satisfying user experiences.

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?

May 1, 2024

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

Gartner generative AI: Shifting gears to GenAI at the 2024 Data & Analytics Summit

April 16, 2024

Gartner generative AI: Shifting gears to GenAI at the 2024 Data & Analytics Summit

Each of the many Gartner D&A summits I’ve attended had its own theme. This year it was all about getting your data ready for GenAI. Here are my takeaways.

RAG

RAG hallucination: What is it and how to avoid it

April 10, 2024

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

Human in the loop: Must there always be one? Another AI horror story

March 21, 2024

Human in the loop: Must there always be one? Another AI horror story

With firms being held liable for their chatbot interactions, it's up to AI to ensure accurate answers. Having to rely a human in the loop is a non-starter.

RAG

GenAI Data Fusion – New from K2view

March 11, 2024

GenAI Data Fusion – New from K2view

AI Data Fusion injects enterprise data into Large Language Models – on demand and in real time – to ground GenAI apps and deliver responses users trust.

K2view RAG

LLM Grounding Leads to More Accurate Contextual Responses

March 4, 2024

LLM Grounding Leads to More Accurate Contextual Responses

LLM grounding is the process of linking linguistic turns of phrase to the real world, allowing LLMs to respond more accurately than ever before.

RAG

Retrieval-Augmented Generation vs Fine-Tuning: What’s Right for You?

February 28, 2024

Retrieval-Augmented Generation vs Fine-Tuning: What’s Right for You?

When your LLM doesn’t meet your expectations, you can optimize it using retrieval-augmented generation or by fine-tuning it. Find out what's best, when.

RAG

Active Retrieval-Augmented Generation – For Quicker, Better Responses

February 20, 2024

Active Retrieval-Augmented Generation – For Quicker, Better Responses

Active retrieval-augmented generation improves passive RAG by fine-tuning the retriever based on feedback from the generator during multiple interactions.

RAG

RAG GenAI: Why retrieval-augmented generation is key to generative AI

February 18, 2024

RAG GenAI: Why retrieval-augmented generation is key to generative AI

RAG transforms generative AI by allowing LLMs to integrate private enterprise data with publicly available information, taking user interactions to the next...

RAG

LLM AI Learning via RAG Leads to Happier Users

February 14, 2024

LLM AI Learning via RAG Leads to Happier Users

By injecting private data into large language models, RAG enhances LLM AI learning for more personalized, precise, and pertinent answers to user queries.

RAG

What is Retrieval Augmented Generation

January 28, 2024

What is Retrieval Augmented Generation

Retrieval-augmented generation is a framework for improving the accuracy and reliability of large language models using relevant data from internal sources

RAG

Gartner LLM report: RAG tips for grounding LLMs with enterprise data

January 28, 2024

Gartner LLM report: RAG tips for grounding LLMs with enterprise data

Learn how to prepare for RAG with this FREE condensed version of the 2024 Gartner LLM report, “How to Supplement Large Language Models with Internal Data”.

RAG

RAG chatbot: What’s it all a bot?

January 1, 2024

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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