Introducing Database AI

Automating Enterprise Search with Database AI

Finance and insurance companies depend on accurate data to make fast and informed decisions. But most of that data lives across complex internal systems. Knowledge workers spend up to 30% of their time searching for information, while over 40% of employee hours go to manual data entry and analysis. Accessing data is often too slow, technical, and limited to a few power users. When every decision counts, these bottlenecks lead to delays, risks, and missed opportunities.

Most enterprise search tools aren’t built for this. They offer keyword-based retrieval or narrow integrations that don’t scale. More advanced systems can search data but don’t understand it, and they can’t adapt to complex schemas or produce industry-specific insights. We saw these problems and built a special AI Agent to solve them. 

We proudly deliver Database AI, which searches complex internal databases and returns answers within knowledge-based workflows. It’s a standout tool that gives non-technical users access to previously inaccessible data.

Introducing Database AI

Database AI is an AI Agent that makes your internal databases searchable with natural language. It connects to your systems, understands complex schemas, and retrieves precise answers in seconds. Need data for loan underwriting, risk modeling, or customer account analysis? Database AI gives your team access without writing complex SQL queries.

We designed it for finance and insurance to handle deep, domain-specific questions that generic AI tools can’t. While typical enterprise search tools rely on keyword matching or shallow integrations, Database AI interprets user intent, maps it to your database schema, and returns structured results with full traceability. It’s trained on your data, aligned with your workflows, and ready for high-stakes environments.

“Data mining remains a powerful tool for decision-making, provided it adheres to these regulatory standards.” — Aakarsh Ramchandani, CSO at RavenPack for Pioneers

It also empowers more people across your organization to use data effectively, not just analysts and engineers. With Database AI, teams can surface answers in plain text or visual formats like charts and tables.

What makes it different is the way it combines vertical fine-tuning with explainability and schema awareness. Built for regulated industries, it includes confidence scores, full audit trails, and clear outputs—so there is a how, what, and why behind every action.

Here is how Database AI outperforms other similar tools on the market:

How Database AI Works

Once connected to your internal database or CRM, Database AI translates natural language into structured queries, pulls relevant data, and formats answers for immediate use. It acts as a system of intelligence on top of systems of record.

Key capabilities include:

• Schema-aware search: Maps plain language to your schema with context and precision.
• Hybrid SQL + vector search: Combines structured and semantic search for better results.
• Real-time querying: Delivers fast responses across even large or complex datasets.
• Feedback loops: Learns from user input (upvotes/downvotes) to improve performance over time.
• Confidence scores: Flags low-confidence answers for human review.
• Audit-ready outputs: Logs every query and action for compliance and traceability.
• Multi-hop handling: Navigates complex joins and relationships to surface multi-step insights.
• Pixel-level data mapping: Delivers outputs with precise context and traceability.
• Visual outputs: Returns data as text, charts, or tables, depending on what the user needs.

All this happens within your secure environment. Database AI is SOC 2 compliant and supports on-prem or private cloud deployment.

Database AI is also available as part of AgentFlow’s Search module. It works alongside other AI Agents to power smarter workflows across document processing, reporting, and decision automation. Together, they deliver end-to-end intelligence across the entire enterprise.

Example of KYB/KYC workflow:

Use Cases in Finance and Insurance

Database AI is purpose-built to support key workflows across finance and insurance. Among many more, example use cases include:

Get Started with Database AI

Database AI empowers your team to search internal data with natural language, eliminate query bottlenecks, and allow your team to focus on high-value work.

Book a demo today to see how Database AI can streamline access and automate up to 90% of your team’s data tasks.

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