Gen AI knowledge management for supercharged enterprise teams

Comprehensive, personalised and accurate
enterprise search

Comprehensive, personalised and accurate enterprise search

At the core of Leena AI Knowledge Management is an Agentic RAG architecture
that selects the optimal RAG pipeline for every employee query.

At the core of Leena AI Knowledge Management is an Agentic RAG architecture that selects the optimal RAG pipeline for every employee query.

Trusted by global Fortune 500 enterprises

Minimize hallucinations, increase accuracy

WorkLM™ fine tuned on 10M+ enterprise prompts

Fact validation utilising multiple models

Data sanity RAG agent

View sources for every search query

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Leverage comprehensive enterprise knowledge

Unify knowledge sources

1000+ out of the box connectors available

Multimodal RAG agent

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Personalization basis dynamic information

Personalization RAG agent

Persistent context across all channels

Intelligent follow ups simulating human conversations

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Agentic AI for enterprise

Multimodal support

Multichannel support

Multilingual support

The highest trust and security standards

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Frequently asked questions

Have a question that is not answered? You can contact us at support@leena.ai

What is Agentic AI for Enterprise Knowledge Management and how does it enhance knowledge workflows?

Agentic AI for Enterprise Knowledge Management refers to autonomous AI systems that leverage advanced natural language processing (NLP) and large language models (LLMs) to streamline the discovery, retrieval, and generation of knowledge within an organization. These AI agents use Retrieval-Augmented Generation (RAG) techniques to dynamically access and incorporate relevant information from internal and external knowledge sources, ensuring that employees have immediate access to accurate, context-aware data to drive decision-making.

How can Generative AI improve Enterprise Knowledge Management through RAG?

Generative AI, when combined with Retrieval-Augmented Generation (RAG), allows Agentic AI to autonomously retrieve pertinent information from vast knowledge repositories and generate contextually relevant responses. This enhances enterprise knowledge management by ensuring that employees can quickly access the right insights, reducing manual searching and improving the speed and accuracy of decision-making processes across departments.

What are the benefits of using AI agents in automating Enterprise Knowledge Management workflows?

AI agents can significantly enhance enterprise knowledge management by automating the process of knowledge retrieval, generation, and distribution. By utilizing Agentic AI systems with NLP and LLMs, organizations can ensure that employees automatically receive the most relevant information without manually searching through disparate knowledge sources, improving efficiency, collaboration, and productivity across teams.

How do AI agents integrate with existing Enterprise Knowledge Management systems?

AI agents, powered by Agentic AI, integrate seamlessly with existing enterprise knowledge management systems and platforms. By using NLP and RAG, these AI agents can retrieve, analyze, and generate relevant knowledge from a variety of sources (e.g., documents, databases, intranets) and present it in real-time. This integration improves knowledge accessibility and enhances decision-making across all levels of the organization.

How does NLP and RAG work together to enhance Enterprise Knowledge Management in Agentic AI?

Natural Language Processing (NLP) and Retrieval-Augmented Generation (RAG) work in tandem within Agentic AI for Enterprise Knowledge Management. NLP enables AI agents to understand and process natural language queries, while RAG allows them to search and retrieve relevant knowledge from large data sets. This combination results in AI systems that generate contextually accurate and insightful responses, streamlining knowledge sharing and improving overall organizational intelligence.

What is knowledge management for enterprises?

Knowledge management involves finding the right information from relevant policies, data, documents, and more, while being able to deliver up-to-date knowledge, no matter where it resides. In addition, being able to deliver it to employees or users with minimal friction, while ensuring the knowledge is authorized for the requester to access it.

How is generative AI transforming knowledge management?

With today's growing enterprise complexity across global organizations, similar knowledge usually resides in multiple documents, or the sources might be unstructured or constitute different formats (ERP systems, Google Drive, spreadsheets, & more). But generative AI can find the most recent and accurate information from such sources, and deliver it in natural language-based conversations. In addition, Gen AI can find new information from sources like resolved tickets and auto-update the right enterprise documents

What are the benefits of an AI employee assistant vs a dedicated knowledge solution?

Humans engage in dialogues no matter the context. With an AI employee assistant platform, employees on the one hand might be satisfied with knowledge served in conversational mode. But on the other hand, they perform some follow-up action or dive deeper into additional information upon requesting the knowledge initially. An automated agent-like solution can serve such needs unlike a knowledge tool

What are related capabilities being offered by modern knowledge management solutions?

Gen AI knowledge solutions are making the knowledge delivery experience more fulfilling by automatically cleaning and organizing raw data from sources for the Gen AI model to understand key knowledge employees request from them. Also, Gen AI is now suggesting relevant actions employees are likely to take after consuming requested knowledge and automating those actions. Finally, the solution offers helpful documents or related projects delivering an enterprise search experience.

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