PAR Technology delivers an agentic operating system that enables smarter, more consistent operations for multi-unit brands across the restaurant, retail and high-volume commerce sectors. The platform brings together mission-critical software, including point-of-sale, digital ordering, loyalty, payments and back-office systems, along with hardware and data, to orchestrate decisions and workflows across systems, locations and guest touchpoints in real time. For PAR Retail, which serves the convenience and fuel retail industry, PAR Intelligence now gives retailers a faster way to understand and act on performance data. Built by PAR on a modern Databricks foundation, PAR turned a fragmented, analyst-dependent data process into a conversational experience that surfaces insights in minutes.
Overcoming fragmented data for faster insights
Before adopting the Databricks Data + AI Platform, PAR's data was spread across disparate systems and formats, making it difficult to analyze consistently at scale. Getting a straight answer to a business question often meant routing it through an analyst and waiting on a backlog.
The challenges went beyond wait times. Historically, PAR faced hurdles across the AI and ML lifecycle, particularly around evaluation, monitoring and operationalizing models. Each of those functions lived in a different tool, which meant stitching together separate systems just to get a model into production and keep it running reliably.
Collaboration suffered as a result. Data science, engineering and analytics teams had to hand off work across environments, which slowed delivery and introduced friction whenever a project moved from one team to the next.
"Before Databricks, data was fragmented across systems and formats, making it difficult to analyze consistently at scale," said Amine Errazi, Product Manager, AI at PAR Technology. "By centralizing data in Databricks, we were able to unify different data types in one place and unlock new analytics and AI use cases on top of a consistent foundation."
Building PAR Intelligence on a modern data foundation
Centralizing on the Databricks Platform gave PAR a modern data and AI foundation for PAR Intelligence: one place to prepare data, evaluate models, run inference and monitor performance. That foundation helps PAR replace a patchwork of disconnected tools while preserving the product strategy, domain expertise and customer-facing experience that make PAR Intelligence distinct.
Enhanced data preparation and model evaluation
With Databricks, PAR can move from data unification to production workflows in a single platform, reducing the overhead of managing separate tools across the lifecycle. This consolidation supports the development of PAR Intelligence.
Improved collaboration across teams
That consolidation also changed how teams worked together. Engineers, data scientists and analysts can now operate in the same shared workspace, iterating on the same data, models and agents without overwriting each other's work.
"Databricks allows multiple team members to work simultaneously on the same agents and workflows," Amine said. "Engineers can focus on orchestration, others on prompt design or evaluation, all while maintaining versioning and avoiding conflicts. This shared environment makes building and maintaining AI solutions fundamentally more collaborative."
Genie enables natural language insights for retailers
With a unified data foundation in place, PAR built PAR Intelligence's Loyalty Agent. This conversational data experience lets customers ask questions about their loyalty and retail performance data in natural language, without writing SQL or waiting on an analyst. Databricks provides part of the modern foundation beneath the experience; PAR Intelligence delivers the customer-facing layer, retail context and workflow relevance that turn that foundation into practical value for operators. PAR Intelligence runs on a broad set of Databricks capabilities:
Genie Agents translates natural-language business questions into analytics workflows, allowing retailers to retrieve insights directly rather than routing requests through an analyst.
Unity Catalog governs who can access which data and capabilities, aligning permissions with different user roles while maintaining consistent oversight across analytics and AI workflows.
AI/BI Dashboards turn Genie's answers into shareable visualizations and reporting so insights extend beyond a single conversation.
Lakebase keeps application and agent data synced with the lakehouse in real time, supporting the low-latency reads the Loyalty Agent needs to respond quickly.
Agent Bricks supports evaluating and optimizing the underlying agents as PAR builds and refines new AI capabilities.
MLflow tracks experiments and versions throughout the agent's development lifecycle, providing PAR with visibility into how the Loyalty Agent evolves.
Model Serving hosts and serves the foundation models behind the Loyalty Agent in production, keeping compute close to the data.
Databricks Lakeflow Jobs orchestrates and automates the data pipelines that keep the Loyalty Agent's underlying data up to date.
That agent architecture extends beyond a single tool. PAR relies on a multi-agent setup built on Databricks’ agent framework and Genie Agents, in which agents orchestrate interactions between users and data, converting natural-language questions into analytics actions. Databricks gives PAR a scalable foundation for model optimization and agent development; PAR Intelligence turns that foundation into a differentiated solution for convenience and fuel retailers.
"While we leverage best-in-class foundation models, grounding those models in our domain-specific data is critical," Amine said. "Convenience and fuel retail is a highly specialized industry, and Databricks enables us to connect AI experiences directly to our enterprise data, so insights are relevant, contextual and actionable for our customers."
From storing data to acting on it
The shift from a traditional to an AI-powered lakehouse changed what PAR's data could actually do. By pairing its lakehouse with Databricks’ analytics and agent capabilities, PAR can now transform raw data into actionable insights and perform root cause analysis in minutes, rather than relying on manual, ad hoc workflows.
PAR evaluates PAR Intelligence across multiple dimensions, including question interpretation, SQL generation, analytics accuracy and visualization quality, with governance and access controls managed centrally through Databricks to ensure consistency as the solution evolves.
Accelerating decision-making with PAR Intelligence
Since implementing the Databricks Platform, PAR has delivered AI-powered experiences that significantly reduce time to insight and improve operational efficiency for analytics and AI delivery.
Questions that once required analyst support can now be answered in minutes.
Databricks has reduced the time required to build and deploy new capabilities by eliminating complex integrations and keeping compute close to the data.
PAR moved from zero to one very quickly, establishing a foundation for innovation that has accelerated internal momentum and reinforced PAR's position as an AI-forward organization in the convenience and fuel retail industry.
Investing in Databricks Training and Certification has helped build that momentum, accelerating onboarding and giving teams the confidence to experiment faster as PAR expands its AI and analytics initiatives.
"Investing in Databricks has increased confidence across teams and improved efficiency by reducing onboarding time and enabling faster experimentation," Amine said.
PAR is also working toward a more centralized data and AI operating model, with plans to continue formalizing best practices and governance as adoption grows.
What's next
Looking ahead, Databricks will remain an important data intelligence foundation, while PAR Intelligence continues to define how those agents translate retail context into decisions, workflows and measurable customer outcomes.
"Databricks will play a critical role as the bridge between data and intelligence," Amine said. "For PAR, the opportunity is to build on that foundation with PAR Intelligence experiences that help retailers access, understand and operationalize data in real time."