Belo Vale Dairy digitizes milk collection and integrates operations with ERP using iPaaS

Laticínio Belo Vale, widely recognized in the consumer market under the Sabor Isis brand, has been operating for over 30 years as a large, family-owned company and a consolidated benchmark in the food consumer goods and agribusiness sector in the Northeast region of Brazil. With its administrative headquarters and main production hub located in Sousa, in the semi-arid region of Paraíba, the company's logistics and industrial operation comprises three modern manufacturing plants and ten distribution centers strategically located throughout the Northeastern states to ensure efficiency in the cold chain and capillary supply to the retail sector. Faced with a scenario of accelerated growth and market expansion, the company encountered the challenge of modernizing its technological governance and migrating from a reactive management model to a data-driven decision-making. To lead this strategic journey of digitalization and operational sustainability, the company has been led by Jederson Martins in the corporate management of Information Technology (IT) since 2017.

Real problem

• Operational bottlenecks: the main bottleneck in the supply chain was in the raw milk collection sector from partner rural producers. Data collection regarding the volume, temperature, and quality of milk received at the end of the chain still depended on physical forms filled out manually on paper.
• Technical limitations: the internal IT team faced severe barriers to orchestrating integrations between legacy systems and external platforms using the traditional tools available at the time. Data flows were rigid, synchronous, and required a high volume of point-to-, increasing the department's response time.
• Operational and business risks: the lack of structured, real-time data created a visible barrier for executive management, limiting a holistic view of the supply chain and hindering Production Planning and Control (PPC). Furthermore, the manual process generated critical risks related to information security, rework, and human error in data entry and reconciliation at the ERP system.
• Financial impact: latency in processing physical information delayed the closing of purchase and inventory reports, impacting cash flow routines, raw material pricing, and strategic supply decision-making.

Solution architecture

The modernization of the data infrastructure at Laticínio Belo Vale was structured around the adoption of Skyone Studio , a platform that unifies iPaaS (Integration Platform as a Service) , lakehouse, and data bus tools to simplify complex software ecosystems .

• Skyone products used: Skyone Studio integration platform running in the cloud layer and acting as central middleware for orchestrating APIs and corporate data.
• Integrations and components: complete replacement of physical forms with a digitized mobile system in the field. Skyone Studio encapsulates the requests generated during data collection, performs semantic mapping of variables (literage, producer identification, collection routes), and automatically feeds the ERP system.
• Technology stack and workflows: use of low-code visual pipelines that connect field-side systems directly to the database and core modules of the corporate ERP, eliminating the need for manual scripts and local servers dedicated exclusively to costly integrations.

Technical challenges and mitigation

• Integration complexity: the main technical challenge was integrating a geographically distributed, field-based agro-industrial process operating in areas with fluctuating network connectivity with a highly rigid, centralized ERP system.
• Development trade-offs: Traditional proprietary connection development would require months of focused effort from senior programmers, generating continuous dependency on custom code that is difficult to maintain. The chosen trade-off was to migrate to low-code visual , which accelerates Time-to-Market and ensures flexibility to modify business rules without breaking the data ecosystem.
• Mitigated risks: the implemented solution addressed the risks of data loss and unavailability of communication buses, offering end-to-end visual monitoring, automated error log handling, and security at the HTTP/HTTPS data traffic layer.

Implementation and rollout

The technology rollout process, led by IT management and supported by Skyone's engineering team, was executed in well-defined chronological stages:

Phase 1: Diagnosis and technical alignment (2023)

Technical immersion with the Skyone team to map the bottlenecks in the milk collection sector and understand the data dictionary required by the ERP system.

Phase 2: Building the pipelines in iPaaS

Configure pre-built connectors and design visual data flows within the Skyone Studio interface, eliminating manual flows based on physical forms.

Phase 3: Approval of integration with the ERP system

Performing tests in a staging environment to validate the sending, transformation, and recording of captured data directly into the corporate ERP modules.

Phase 4: Rollout and continued training

Activation of the integrated production system in the dairy's logistics routines and the start of technical training programs promoted by Skyone to ensure the autonomy of the internal IT team in the platform's evolution.

Measurable results

• 100% digitization of milk collection: definitive replacement of paper and complete elimination of manual forms in the raw milk collection sector.
• Significant reduction in development time: a drastic reduction in hours spent on traditional connection development and corrective maintenance routines by the IT team.
• Maximizing system agility: faster, more secure, and transparent connections integrated directly into the company's main ERP system.
• Scalability and integration flexibility: achieving architectural freedom to clone, customize, and scale new data integrations to other strategic areas (tax, commercial, and logistics) of the company.
• Internal technical maturity: raising the level of technical proficiency of the internal team through training and specialized support offered by Skyone.

Lessons learned

• Autonomy and focus on the business: adopting low-code integration tools and iPaaS decentralizes operational bottlenecks in the technology area, freeing the IT team from repetitive support tasks and allowing them to focus on digital solutions that generate direct value for the business.
• Eliminating peripheral silos: manual processes in manufacturing and agribusiness industries create hidden information silos. Consolidating field data in real time within the ERP system is essential for management driven by accurate performance indicators.
• Data-ready infrastructure and artificial intelligence: structuring a stable data bus using Skyone Studio paves the necessary foundation for Laticínio Belo Vale to safely execute its future plans involving advanced data analysis and the adoption of Artificial Intelligence (AI) in the agro-industrial ecosystem.

FAQ

How did Laticínio Belo Vale eliminate manual processes in milk collection?

The Belo Vale Dairy (Sabor Isis) used Skyone Studio's iPaaS solution to digitize its raw milk collection sector, replacing physical paper forms with automated workflows integrated directly into the company's corporate ERP system.

What are the advantages of Skyone Studio for IT teams in the food industry?

Skyone Studio offers a low-code visual interface that reduces the time spent on manual development and maintenance of complex system integrations. This provides flexibility and agility to connect field operational data to the core ERP, optimizing IT team time and reducing operational code maintenance costs.

How does Skyone's iPaaS platform prepare companies for the use of Artificial Intelligence?

The Skyone Studio iPaaS platform centralizes, standardizes, and automates the flow of information from multiple enterprise sources and applications. By breaking down data silos and structuring clean integration pipelines, the solution creates the mature analytical foundation and governance needed to power Business Intelligence (BI) and generative artificial intelligence projects.