Fragmented systems hide inefficiencies. Your WMS, ERP, and logistics platforms don't speak the same language, making root cause analysis impossible.
Manual reporting drains operational capacity. Your team spends more time creating reports than improving operations.
Can't optimize what you can't measure consistently. When "on-time delivery" means different things in different systems, you're flying blind.
Preql's AI agents integrate and standardize operational data from every source, giving you accurate visibility and actionable insights.
Unified operational metrics. Define KPIs like "on-time delivery," "inventory turnover," or "production efficiency" once, see them consistently everywhere.
Identify bottlenecks automatically. AI agents analyze operational data to surface inefficiencies and optimization opportunities you couldn't see before.
Automate operational reporting. Free your team from manual report generation so they can focus on process improvement.
Identify where delays are occurring across your entire supply chain. Preql connects data from suppliers, warehouses, logistics providers, and production facilities to show you exactly where to focus improvement efforts.
Understand true inventory velocity across all SKUs and locations. Connect warehouse data with sales forecasts and production schedules to optimize stock levels and reduce carrying costs.
Track production metrics across multiple facilities with consistent definitions. Identify which lines are underperforming, which processes create bottlenecks, and where to invest in capacity improvements.
Optimize staffing by understanding patterns in workload, productivity, and resource allocation. Connect HRIS data with operational metrics to right-size teams and reduce overtime costs.
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.