Unified Research Technologies
URTech provides an agentic-based AI system that runs locally within a company's data silo to learn the structure and meaning of proprietary datasets. The platform uses specialized agents to generate SQL queries, perform exploratory analyses, and suggest new hypotheses, all while keeping data secure on-premises. It is designed for data analysts and research teams who need to explore complex data without extensive manual SQL coding.
- AI Agents
- Data & Analytics
- Artificial Intelligence
- Enterprise Software
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Organizations often struggle to extract meaningful insights from their data because it requires deep SQL expertise and an understanding of complex, proprietary data schemas. Traditional analytics tools are either too rigid to handle ad-hoc questions or require significant manual effort to write and debug queries, limiting data accessibility for non-technical stakeholders.
Solution
URTech provides an agentic-based AI system that runs locally within a company's data silo, learning the specific structure, relationships, and meaning behind the user's data over time. The platform consists of three collaborating agents: a Query Generator that writes and refines SQL queries based on natural language questions, an Analysis Engine that transforms query results into summaries and visualizations, and an Interrogation Driver that proposes new hypotheses and explores relationships between variables. The system comes pre-trained in SQL best practices and basic data analytics, then fine-tunes itself by storing successful queries and their outcomes for future reference. An overseer agent coordinates the workflow and keeps a human in the loop to ensure the system stays aligned with user priorities and research goals.
Target Audience
Primary users are data analysts, business intelligence teams, and research professionals who work with complex, proprietary datasets and need to generate queries and explore data without writing extensive SQL code manually.
Features
- Pre-trained local language model with SQL best practices and standard data analytic techniques
- Query Generator that learns schema names, table relationships, and variable meanings through interaction
- Self-maintaining repository of successful queries that improves accuracy and efficiency over time
- Analysis Engine that converts query outputs into data summaries and visualizations
- Interrogation Driver that suggests unexplored variable relationships and generates follow-up hypotheses
- Overseer agent that coordinates agent collaboration and maintains human oversight
- Runs entirely on-premises within the user's network, ensuring data never leaves the local environment