Data to Insights AI
DataToInsights provides an AI-powered intelligence layer that connects fragmented enterprise data sources—including ERP, POS, inventory, and spreadsheets—so users can ask plain-English business questions and receive answers with full data lineage. The platform automates data preparation through agentic workflows and integrates with 100+ data sources, warehouses, and BI tools. It targets mid-to-large enterprises seeking governed, context-aware AI insights.
- Data & Analytics
- Artificial Intelligence
- Enterprise Software
- AI Agents
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Enterprises struggle with fragmented data spread across multiple systems—ERP, POS, inventory, sales, and spreadsheets—which prevents AI models from understanding business context. This fragmentation leads to inaccurate insights, untrustworthy answers, and significant manual data preparation effort before any analysis can occur.
Solution
DataToInsights builds an "intelligence layer" that connects heterogeneous data sources, business definitions, rules, and workflows so AI systems can comprehend the organization's operational context. Users can ask plain-English questions like "Why did fill rate drop last quarter?" and receive answers synthesized from connected systems, with every figure traceable to its source row. The platform includes agentic workflows that automate data preparation—such as profiling, validation, and query generation—keeping insights accurate and adaptive. By creating a governed, unified business context, DataToInsights enables AI to surface what matters and take action based on trusted, verifiable data.
Target Audience
Primary users are data engineering and analytics teams at mid-to-large enterprises that need to unify scattered business systems and provide reliable, context-aware data for AI applications and decision-making workflows.
Features
- Plain-English business question interface that retrieves answers from integrated sales, inventory, ERP, POS, distributor, and spreadsheet systems
- End-to-end data lineage that traces every reported figure back to its original source row for auditability and trust
- Agentic workflow automation for data preparation, including profiling, validation, and AI-driven query generation
- Native connectors for PostgreSQL, MySQL, MS SQL Server, MongoDB, Snowflake, Databricks, Salesforce, Excel, CSV, Notion, SharePoint, and HubSpot, with support for 100+ data sources, warehouses, and BI tools
- Multi-layer architecture including Understanding, Semantic, Integration, and Agentic Understanding layers for contextual data mapping and autonomous decision-making
- Governance layer that maintains consistent business definitions and rules across the enterprise data stack