Disparate systems. Legacy infrastructure. Rigorous compliance. Our customers operate where mistakes are expensive, and Preql catches them automatically.
The culprit isn't the Al, it's the data. The most valuable data in your business is trapped in disparate legacy systems that don't talk to each other. Your Al might be state-of-the-art, but if it's working with inconsistent definitions, outdated pipelines, or is missing business context, it's just a new way to serve up bad data.
The reality:
Homegrown and legacy systems rarely speak the same language
Analysts spend 70% of time prepping data in spreadsheets
Copilots and forecasting models fail without clean input
Preql automates the hardest part of AI adoption: preparing structured, trustworthy data. Our agentic platform continuously cleans, aligns, and contextualizes data from every system — so your copilots, analytics, and workflows deliver results from day one.
Plug into ERP, CRM, HR, and expense platforms in minutes
Agents resolve mismatches, anomalies, and schema drift automatically
Structured outputs flow seamlessly into copilots, dashboards, and workflows
Ongoing governance with audit trails and drift alerts
Preql's Al agents don't just serve data - they understand your business context, apply it consistently across systems, and catch errors before they reach your analytics or LLMs.
What makes it different:
Proactive, not reactive: Errors are caught and resolved before they propagate through your stack
Context-aware: Agents learn your business logic and apply it consistently across every dataset
Self-improving: The system gets smarter as it sees more patterns, automatically adapting to your evolving data lanascape
Preql automates the hardest part of AI adoption: cleaning, reconciling, and contextualizing messy enterprise data. Our AI agents transform fragmented ERP, CRM, HR, and expense data into structured, auditable, AI-ready pipelines that scale across the enterprise.
Traditional ETL tools move data, but they don’t understand business context. Preql is semantic and agentic: it reconciles mismatched records, aligns metrics, and maintains governance so data is both technically accurate and business-relevant.
We partner with a wide range of enterprise leaders — from AI and data teams to CIOs, CFOs, and CEOs. Many of our earliest deployments have been with finance, where data reconciliation is most painful, but Preql is designed to support cross-functional initiatives spanning finance, operations, compliance, and IT.
Yes. Preql is purpose-built for enterprise deployment, with role-based access control (RBAC), encryption in transit and at rest, audit trails, and flexible deployment options (cloud or within your environment). Compliance, governance, and scale are core to our architecture.
AI copilots and automation tools are only as good as the data they run on. Preql ensures your data is reconciled, trusted, and semantically defined so copilots, BI dashboards, and automated workflows generate results you can rely on.
We start with quick integrations into your existing systems (ERP, CRM, HR, expense). Within weeks, Preql delivers reconciled, AI-ready data for key workflows. From there, we scale progressively across business units while maintaining strict governance and compliance.