In today’s data-driven world, businesses are sitting on a goldmine of insights. Still, the tools to access this data often remain locked behind technical know-how, dashboards, and SQL queries, accessible only to analysts and engineers.
We set out to change that.
Introducing Our Conversational AI Agent for Databases
We’ve developed an AI-powered agent that enables any business user to “talk” directly to databases using natural language, no SQL, no BI tool expertise, no wait time.
Whether you want to:
- Know this quarter’s revenue vs. last quarter
- Compare sales across geographies
- Analyse customer churn
- Or even generate a predictive trend line
All you have to do is ask.
Why This Matters for Business
Business users spend too much time waiting for insights by creating tickets, interpreting dashboards, or trying to extract meaning from static reports. By the time answers arrive, the question has often changed.
Our AI agent compresses that cycle into seconds.
Business Benefits:
- Faster Decision-Making: Instant answers to data questions
- Empowered Teams: Non-technical users can independently explore data
- Reduced Burden on Data Teams: Fewer ad-hoc queries and tickets
- Better Use of Existing Data Investments: Unlock true ROI from your databases and BI platforms
What the Agent Can Do
Our AI agent is not just a chatbot. It’s a context-aware analytics interface that sits on top of your data layer. Here’s what it brings:
- Natural Language Understanding → “Show me top 10 SKUs by profit margin in the last 6 months”
- Cross-database Querying → Works with cloud warehouses, relational databases, and operational stores
- Advanced Reasoning → Calculates growth rates, aggregations, rolling averages, YoY comparisons
- Graphical Output → Line charts, bar graphs, pivot tables, etc., chosen based on intent
- Conversational Context → Supports follow-ups like “Just for Asia Pacific” or “Exclude outliers”
LLM-Independent and Cloud-Agnostic
Unlike typical AI tools tied to specific cloud vendors or LLM APIs, our agent is LLM-independent by design:
- Deploy with your preferred LLM — Open-source (e.g., Ollama, LLaMA, Mistral) or enterprise (OpenAI, Azure OpenAI, AWS Bedrock, etc.)
- Fully On-Prem Deployable — For industries with strict data residency and security policies
- Cloud-Agnostic Architecture — Works seamlessly on AWS, Azure, GCP, or hybrid edge deployments
- No Vendor Lock-In — Bring your model, data lake, and compute environment
This makes our solution ideal for BFSI, Energy, Telecom, and Public Sector organisations with regulatory or operational constraints.
Use Cases Across Industries
Energy & Utilities
- “Give me the daily downtime trend by region”
- “What’s the average output per solar panel last month?”
Telecom
- “How many tickets breached SLA last week by customer segment?”
- “Compare churn between prepaid and postpaid users”
BFSI
- “What’s the NPA trend for the SME segment?”
- “How do Q1 collections compare YoY?”
Built for Enterprise
We designed the agent to be enterprise-ready from day one:
- Role-based Access Control
- Governed Query Generation to avoid unsafe or costly operations
- Data Source Abstraction to support hybrid and multi-cloud environments
- Custom Vocabulary to align with business-specific terms and KPIs
- Continuous Learning Loop based on user corrections and feedback
The Road Ahead
We’re expanding the agent’s capabilities to support:
- Scheduled Reports via Conversation
- Multi-turn Dialogue for deeper exploration
- Integration with collaboration tools like Teams and Slack
- Embedded Mode for internal portals and apps
Natural language is the new interface for data. If your business teams can talk to their database like they talk to a colleague and get reliable, real-time answers, it changes how decisions are made.
Faster. Smarter. Scalable.
Written by Aashish Agarwal
