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AI assistant for providing answers on the legislative framework
3
reduction in time spent searching for information
times
AI-powered chatbots and the LLM
Customer
Atomic Holding of Russia
CHALLENGES/FEATURES
A comprehensive knowledge base on occupational safety and health for finding answers
The need to consider the structure of documents and the relationships between them and their sections
Providing answers only based on documents with links to relevant sections
High requirements for the accuracy of answers
The need to consider the structure of documents and the relationships between them and their sections
Providing answers only based on documents with links to relevant sections
High requirements for the accuracy of answers
Develop an AI assistant integrated into Telegram to provide answers on legal matters.
The AI assistant should determine user intent and answer questions based on information in the knowledge base, providing links to information sources and document templates when generating answers.
The AI assistant should determine user intent and answer questions based on information in the knowledge base, providing links to information sources and document templates when generating answers.
Task
solution
Technical solution
The AI technical support assistant is implemented in Telegram using the open-source Langchain/Langgraph libraries and the open-source Gemma3 language model.
The technical solution includes:
1. An adaptive document loading and indexing mechanism that takes into account their structure.
2. Creation of knowledge bases for hybrid search (based on keywords, semantic proximity, and graph search).
3. Creation of a query processing graph based on an extended RAG to ensure the accuracy of responses and significantly reduce hallucinations.
4. Automatic query monitoring and evaluation using the Langfuse query logging and tracing tool.
The technical solution includes:
1. An adaptive document loading and indexing mechanism that takes into account their structure.
2. Creation of knowledge bases for hybrid search (based on keywords, semantic proximity, and graph search).
3. Creation of a query processing graph based on an extended RAG to ensure the accuracy of responses and significantly reduce hallucinations.
4. Automatic query monitoring and evaluation using the Langfuse query logging and tracing tool.
Result
Business values
Reducing information search costs:
Relevance:
An automated virtual assistant reduces information search time by 3 times
Answers are provided based on current information from an automatically updated database.
The solution is scalable to any workload and additional documentation.
High speed of request processing:
Scalability:
Quick responses increase user loyalty.
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