Case Study
Conversational data
at enterprise scale
How GoLabs revolutionized data interaction for Gacela's SaaS platform, replacing 40-minute manual SQL reports with a RAG-powered AI interface that delivers actionable insights in under 2 seconds.
Project overview
Industry
SaaS / Data Intelligence
Year
2024
Services
AI Development · RAG Systems
Stack
Python · GPT-5 · Llama Index · FastAPI
The Challenge
Breaking down the barriers to data accessibility
Gacela faced significant obstacles in delivering intuitive data experiences. Manual processes and technical barriers created friction between users and valuable business insights, resulting in a 65% user frustration rate.
Time-consuming manual reports
Users spent 40+ minutes manually generating reports from structured databases, creating significant productivity bottlenecks.
Complex query requirements
Technical SQL knowledge was required for data retrieval, locking critical business insights away from non-technical users.
Reactive decision making
The platform’s inability to deliver insights quickly restricted strategic agility, forcing teams to analyze data after decisions were already made.
RAG Pipeline Architecture
The Solution
An intelligent data conversation platform
RAG Implementation
Retrieval-Augmented Generation for contextual AI responses grounded in actual company data schemas.
Natural language chat
An intuitive interface that allows users to ask questions in plain English and receive instant, accurate responses.
Intelligent Query Processing
AI converts intent to optimized SQL queries, securely fetching from PostgreSQL and interpreting the results.
Secure local optimization
Ollama-based local processing ensures enterprise data privacy while reducing API costs for sensitive operations.
Execution
Architecture
Mapped existing data sources and built the foundation
Vectorization
Ingested schemas and built Llama Index retrieval system
AI Integration
Configured GPT-5 and Ollama for secure language processing
Refinement
Rigorous testing against known SQL reports for accuracy
Deployment
Launched WebSocket chat interface to business users
Building a secure, conversational bridge to data
The challenge was transforming scattered database tables into a unified, searchable knowledge base without compromising enterprise security. We began by indexing the existing schemas and using Llama Index to create a robust vector database that powered the semantic search layer.
For the cognitive layer, we utilized GPT-5 for its unparalleled intent recognition, while deploying Ollama locally for privacy-critical processing operations. A FastAPI backbone connected the intelligence layer to PostgreSQL via SQLAlchemy, with WebSockets enabling the real-time conversational UI.
"By embedding AI directly into our platform, we improved operational efficiency and strengthened our market position. Golabs delivered a smarter, faster platform that our users love."
Technology stack
Results
Transforming scattered data into business value
Time to Insight
0%
Reduced complex report generation from 40+ minutes to under 1 minute, eliminating manual bottlenecks.
User Accessibility
0%
Democratized data access across departments, growing independent user data exploration from 20% to 92%.
Query Accuracy
0%
AI responses perfectly match business context, reducing misinterpretation and improving decision confidence.
By embedding AI directly into the SaaS platform, Gacela moved from reactive report building to proactive conversational analytics. Critical business decisions now happen in minutes rather than days.
Strategic Agility
0×
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