Hadaly is an AI-powered platform that streamlines corporate transactions and M&A due diligence by helping teams analyze large volumes of documents and extract actionable insights quickly. To strengthen this capability, GoML developed an advanced AI chatbot system that enables secure, intelligent interaction with data rooms and enterprise documents.
Problem: traditional systems limit AI chatbot system adoption
Due diligence workflows rely on manual document review and basic keyword search, which reduces the effectiveness of an AI chatbot system. The system lacks context awareness struggles with complex multi-document queries and cannot handle follow-up interactions efficiently. It also fails to enforce strict document-level access control and often shows weak alignment between user queries and results. These gaps create friction and limit adoption of the AI chatbot system in enterprise workflows.
Solution: enterprise AI chatbot system for secure document intelligence
GoML built a Gen AI powered AI chatbot system that enables secure, intelligent querying across multiple data rooms with strict access control. This solution leverages GoML’s Agentic AI Accelerator to manage context, orchestrate multi-step query workflows, and ensure accurate response generation.
The AI chatbot system uses Retrieval Augmented Generation, LLMs, and hybrid search to deliver accurate, source-backed answers.
Conversational AI chatbot system and context management
Key improvements in the AI chatbot system:
- Better interpretation of user intent
- The AI chatbot system supports follow-up queries without restarting
- Users can refine inputs within the same AI chatbot system session
- The AI chatbot system supports English and French queries
Document intelligence powered by AI chatbot system
The AI chatbot system processes enterprise documents at scale
- Handles PDF, Excel, CSV, and text files
- Improves retrieval accuracy within the AI chatbot system
- Combines vector search and keyword search
- Improves relevance of AI chatbot system responses
- The AI chatbot system generates responses only from available documents
Secure AI chatbot system with access control
Security is built into the AI chatbot system
- The AI chatbot system restricts users to permitted documents
- Search results are controlled within the AI chatbot system
- The AI chatbot system blocks restricted access attempts
- Ensures the AI chatbot system does not expose unauthorized data
- All AI chatbot system responses are traceable
Search orchestration in AI chatbot system
The AI chatbot system integrates multiple intelligent components
- Understands query purpose before processing
- Combines semantic and keyword retrieval
- Improves relevance of AI chatbot system results
- Generates answers using LLMs with context
- The AI chatbot system maintains conversation history
Interactive experience with AI chatbot system
The AI chatbot system provides a simple interface
- Users engage directly with the AI chatbot system
- Answers are shown in bullet points or tables
- The AI chatbot system delivers responses quickly
- Maintains interaction history within the AI chatbot system
LLMs via Amazon Bedrock
- Backend using FastAPI
- Vector database using OpenSearch
- Session storage using DynamoDB
- Document storage using S3
- Frontend using Streamlit
Quality assurance for AI chatbot system
Testing ensures accuracy and reliability
- High query classification accuracy
- High document retrieval precision
- Zero unauthorized access cases
- Performance validation under load
Impacts
- 3x-5x faster due diligence workflows
- 90% plus accuracy in document retrieval
- Zero data leakage with secure AI chatbot system
- 60-80% reduction in repeated queries
About
Before Gen AI and after Gen AI
“With the AI chatbot system, Hadaly transformed due diligence into a faster, secure, and insight-driven process that enables teams to make better decisions efficiently.”
Prashanna Rao, Head of Engineering, GoML
Key takeaways for AI chatbot system adoption
Common challenges
- Manual workflows limit AI chatbot system impact
- Lack of secure architecture
- Difficulty handling complex queries
Practical guidance
- Adopt AI chatbot system for enterprise search
- Combine semantic and keyword retrieval
- Ensure strong access control in AI chatbot system
- Use RAG to improve AI chatbot system accuracy
- Start with high-impact use cases like financial and legal analysis
Ready to build AI chatbot system solutions
Partner with GoML to build scalable AI chatbot systems for secure document intelligence and enterprise workflows using Gen AI with AI Matic.
