About Heritage Grocers Group
Heritage Grocers Group is one of the leading specialty ethnic food retailers serving Hispanic communities across the United States. Headquartered in Ontario, California, the company operates multiple grocery brands including Cardenas Markets, Tony's Fresh Market, Los Altos Ranch Market, and El Rancho Supermercado across more than 115 stores in six states.
Every day, these stores generate large volumes of operational and customer data across point-of-sale systems, merchandising, finance, supply chain, HR, and loyalty platforms.
Between 2022 and 2024, the company expanded rapidly through acquisitions and new store openings. While the business growth was strong, the underlying data environment struggled to scale at the same pace.
The business challenge
As Heritage Grocers Group continued expanding, every newly acquired banner introduced different systems, schemas, and reporting structures. Data was spread across disconnected platforms that had been implemented at different times with little standardization between them.
Many of the existing pipelines were either manual or semi-automated, which meant internal teams constantly had to intervene just to keep processes running. Reporting cycles that should have taken hours were stretching into days and sometimes weeks.
The organization lacked a single enterprise-wide view across all banners, making it difficult for leadership teams to make timely operational and strategic decisions. Engineering teams were spending most of their time maintaining integrations instead of building new capabilities.
As Prabhas Coswatte, Chief Operating Officer, explained: "Understanding the unique purchasing preferences of the Texas customer compared to those in Chicago is crucial. The quicker we grasp this, the better we can cater to each community's needs."
Using traditional modernization approaches, the estimated timeline for a complete transformation was close to three years, which simply did not align with the pace of business growth.
Legacy environment
Before modernization, the company's environment included:
- On-premises SQL systems across multiple retail banners
- Isolated point-of-sale and transaction systems at store level
- Microsoft D365 for ERP and financial operations
- Separate merchandising, loyalty, and employee management platforms
- Manual and semi-automated data pipelines requiring constant maintenance
- No centralized enterprise data model connecting all brands
Why change was needed
The turning point came when the organization attempted to standardize reporting across recently acquired banners. Every acquisition required months of manual mapping, profiling, and integration work. Over time, this created growing technical debt and slowed the business down.
Without a scalable and repeatable integration strategy, Heritage Grocers Group could not continue growing its data capabilities at the same speed as its retail footprint. The business needed a modern foundation that could support future acquisitions without rebuilding integrations from scratch every time.
The OpenOntos approach
OpenOntos deployed its AI-assisted Data Lake Accelerator to help Heritage Grocers Group modernize its data foundation quickly and securely. The platform was designed specifically for enterprises managing large-scale data environments with multiple source systems and ongoing operational changes.
AI agents were used to automate repetitive tasks such as:
- Data profiling
- Quality assessment
- Standardization
- Schema normalization
- Migration preparation
At the same time, human experts remained involved throughout the process to validate outputs and ensure production-level accuracy.
The entire implementation was deployed inside Heritage Grocers Group's Azure cloud environment using:
- Azure Storage
- Azure OpenAI
- Microsoft Fabric
No data left the organization's private environment. The outcome was a governed, analytics-ready data platform that the internal team could continue managing and extending independently.
Migration & modernization strategy
OpenOntos worked closely with the internal IT and business teams to design a modernization strategy focused on operational outcomes rather than just technical delivery. Key implementation steps included:
- Designing a Microsoft Fabric aligned architecture built for future acquisitions
- Building ingestion pipelines across all critical business domains
- Applying AI-assisted profiling and standardization across stores and banners
- Standardizing enterprise definitions across POS, HR, budgeting, merchandising, D365, and loyalty systems
- Automating the processing and classification of three years of historical transaction data
- Creating reusable onboarding patterns for future stores and acquisitions
Technical transformation highlights
The scale of the implementation completed within 60 days included:
- 3 billion item transactions processed and organized for analytics
- 1.3TB of historical data standardized across hundreds of transaction event types
- Unified data across more than 115 stores operating in six states
- AI-assisted automation completed nearly 70% of profiling and standardization activities, while experts validated and refined outputs for full production accuracy
Business outcomes
The modernization delivered measurable operational and financial improvements:
- Project delivery timeline reduced from three years to approximately one year
- Reporting latency reduced from days and weeks to just hours
- Engineering effort reduced by nearly 60 to 70%
- More than $500,000 in annual operational cost savings
Operational impact
Teams across the organization could now access trusted business data within hours instead of waiting days for reports. This significantly improved:
- Pricing optimization
- Promotional planning
- Inventory forecasting
- Operational issue resolution
- Cross-banner reporting visibility
New store onboarding also became much more manageable because the organization now had reusable integration patterns instead of rebuilding workflows from scratch every time.
The modernization also created a foundation for future initiatives including:
- HR analytics
- Supply chain optimization
- Customer personalization
- AI-driven reporting and forecasting
Key benefits achieved
- Unified all banners and stores into a single governed data platform
- Created a production-ready analytics foundation for enterprise reporting
- Reduced manual integration and maintenance overhead significantly
- Built scalable onboarding processes for future acquisitions
- Enabled long-term readiness for AI, analytics, and personalization initiatives
Conclusion
For Heritage Grocers Group, data had gradually become a bottleneck to growth instead of supporting it. OpenOntos helped the organization change that within a short implementation window.
In just 60 days, the company established a scalable and modern data foundation that improved operational visibility, reduced costs, accelerated reporting, and simplified future expansion.
Most importantly, the organization moved from reactive integration work to a repeatable modernization model that becomes easier to scale with every future acquisition.