Knowledge Base AI Bots
Effortlessly integrate diverse enterprise data sources to enhance AI responses with the structured knowledge recall mechanism provided by RAG.
Encountered AI Challenges
Context Limit in AI
LLMs struggle with extensive data analysis.
Knowledge Scatter
Scattered organizational knowledge coordination.
Domain Knowledge
Limiting their ability to provide accurate responses.
Concern AI Projects
Poor data quality hampers AI in cleansing for better outcomes.
Diverse Knowledge Sources
Robust Knowledge Integration
Our platform offers versatile methods for incorporating knowledge, allowing users to upload documents in various formats such as doc, pdf, md, txt, csv, xls, and more.
Data Structuring
In addition to accommodating unstructured data like traditional documents, our platform also supports structured data such as tables and Q&A formats as part of its knowledge base.
Third-party Integrations and API
Easily integrate knowledge from third-party applications like Notion, Dropbox, Google Drive, and more, expanding the sources of information for your AI.
Efficient Knowledge Management
Online Knowledge Editing
Edit uploaded knowledge directly online, simplifying the modification process.
Web Knowledge Update
Easily update web page information with just one click, eliminating the need for re-adding.
Knowledge Slicing
Streamlined knowledge slice management for enhanced control.
Enhancing Knowledge Value
Optimal Knowledge Architecture
Our structure optimizes editing, generates Q&A efficiently for RAG architecture and LLM fine-tuning.
Improved Knowledge Retrieval
Improved knowledge recall is achieved through the structured storage method of "Q&A," enhancing the accuracy of retrieval processes.
Streamlined Bot Training
Refining Bot proficiency through chat history analysis and iterative "Q&A" refinement drives continuous performance enhancement.
Simplify LLM Fine-Tuning
Utilize the structured "Q&A" knowledge directly for LLM fine-tuning, simplifying the fine-tuning process.
Powerful Knowledge Embedding
Quality Knowledge Embedding Model
Access the world's leading embedding model for superior semantic matching of knowledge, ensuring accuracy and relevance.
Mixed Retrieval Mode
Dense + Sparse Vector Retrieval Enhanced accuracy through combined vector and keyword search.
Vector Retrieval Analysis
Knowledge Retrieval Test Assess the effectiveness of knowledge retrieval by conducting direct tests.
Secure Knowledge Storage
LarkBots employs cutting-edge technologies like transmission encryption, security encryption, and account data isolation to maintain your data in a highly secure state. With multiple backups and robust cloud platforms, we guarantee rock-solid data security. Choose us for peace of mind and unwavering trust in your data's safety.