AI Solution to Revolutionize Knowledge Management
Exploit your Knowledge, rapidly, with a high ROI.
KAI is an AI Solution for Knowledge Management.
KAI provides an AI platform to automate the Knowledge Management of your databases.
Nowadays, enterprises and companies have phenomenal quantities of random quality data.
KAI’s solution works on:
Unstructured Data
High-Volume Databases
Multiple Formats
Various Content
How it Works
KAI’s AI Solution for Knowledge Management is a middleware.
We provide you with an API to which you can connect your databases and that integrates and adapts to your tools.
1 Solution, 2 Modules
KAI AUDIT
Control your Data
- Automatically and continuously analyses and diagnoses your knowledge with AI.
- Identifies contradictory data, duplicate documents, obsolete files, missing subjects, as well as their exact placements, even as new information emerge.
- Provides an AI-assisted action plan for you to easily update and clean your data over time.
KAI SEARCH
Exploit your Knowledge
- Speeds up information retrieval by enabling you to ask questions and search for information in natural language.
- Provides reliable, complete, and comprehensive answers to the search queries, using generative AI.
- Facilitates instant access to the documents that contain the information you need.
KAI Audit and KAI Search modules can be used together or separately, depending on your needs.
End-user applications can be connected to KAI by API to address different use cases.
KAI Audit analyzes documents and reasons like a human in order to ensure the quality and accuracy of the output delivered by KAI Search.
To transform your data into knowledge, kai is your guide.
Why KAI?
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KAI's Neural Semantic Graph
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RAG
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Document Slicing
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Semantic slicing - slicing based on document creation logic.
=> Semantic meaning intact.
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Basic, arbitrary chunking.
=> Loss of meaning.
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Document Analysis
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Automatic detection of concepts and themes.
Content vectorization.
Generated meta.
⇒ Keeps semantic context.
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Basic vectorization.
Embedding
=> Loss of context.
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Document Indexing
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Creation of the semantic graph, following concepts and themes.
=> Creation of global semantic context.
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Pooling of raw vectors.
=> No semantic links between documents.
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User Search
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Analysis of search via semantic graph.
Retrieval of the right documents.
=> Generation of contextualized response.
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Retrieval of the chunks that are closest to the user's query.
=> Generation of answers with chunks, possibility of increased hallucinations.
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Document Cleansing
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Use of semantic graph to detect contradictory documents with respect to themes and concepts.
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Not Applicable
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Knowledge Mining
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Via prompt factory + Semantic graph
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Not Applicable
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Immediate Impact
Operational Efficiency
KAI’s middleware solution, with the KAI Audit and KAI Search modules, empowers companies to optimize knowledge management. By automating document audits and simplifying content updates, KAI Audit saves valuable time, reduces errors, and ensures that teams always have access to accurate, up-to-date information. Meanwhile, KAI Search provides fast, intelligent search capabilities, making it easy for users to find reliable, complete, and comprehensive answers using natural language. This combination enhances productivity and supports data-driven decision-making, helping businesses stay competitive.
Financial Performance
KAI’s automated audit and search capabilities directly translate to cost savings for clients. By reducing the manual hours needed to locate and update documents, KAI Audit cuts down on operational expenses tied to content management. The accuracy and efficiency of KAI Search also lead to faster, better-informed decisions, helping companies avoid costly errors associated with outdated or inaccurate information. As a result, KAI drives significant operational cost reduction and boosts productivity, maximizing the return on investment for clients.
Environmental Responsibility
KAI’s document auditing and knowledge management solution helps companies reduce their environmental footprint. By identifying duplicate and outdated documents for teams to delete, KAI Audit reduces the need for excessive digital storage and conserves server energy, lowering overall data processing demands. Additionally, more efficient document retrieval means fewer resources are spent on repetitive searches, minimizing energy use on data servers. These streamlined processes contribute to lower carbon emissions associated with storage and processing, supporting corporate ESG compliance goals and promoting a greener approach to information management.