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Industry · Manufacturing

Industrial operations
made intelligent.

Manufacturing technology operates at two speeds simultaneously — the shop floor where a sensor reading is obsolete in milliseconds, and the enterprise where data from thousands of machines must inform decisions across supply chains, dealer networks, and financial planning. Connecting those two worlds without disrupting either is the challenge Shelorve is built to do.

The Challenge

What makes manufacturing technology different

OT/IT integration complexity
Operational technology — PLCs, SCADA systems, MES, and the industrial protocols they run on — was not designed to integrate with enterprise IT. OPC-UA, MQTT, and proprietary vendor protocols are not REST APIs. Connecting shop floor telemetry to AWS data pipelines requires both OT expertise and cloud architecture expertise — a combination Shelorve brings to every manufacturing engagement.
Legacy ERP debt
Manufacturing organizations run some of the oldest ERP environments in enterprise technology. SAP systems that have been customised over twenty years of business change. Legacy MES platforms that were built when the plant was designed and have not been replaced because the plant cannot stop. The dependencies in these systems are enormous and almost entirely undocumented. CodeSight™ maps them before any modernization begins.
Supply chain data fragmentation
Demand data lives in one system. Inventory data in another. Supplier capacity data in a third. Customer order data in a fourth. Supply chain decision-making is impaired not by a lack of data but by an inability to see all the relevant data in one place at the same time. The data platform problem is the supply chain problem.
Predictive maintenance ROI
Unplanned downtime in manufacturing is measured in tens of thousands of dollars per hour. Predictive maintenance AI — using machine telemetry to predict failure before it occurs — has a clear and measurable ROI. But it requires a real-time data pipeline from the shop floor, a training dataset large enough to learn failure patterns, and a model that operations teams trust enough to act on. Shelorve builds all three.
Quality and compliance standards
Manufacturing organizations operating under ISO 9001, ISO 27001, or CMMC requirements face the same architectural challenge as every other regulated industry — compliance cannot be retrofitted after the system is built. Audit trails, access controls, quality management data flows, and cybersecurity controls must be designed in from the first infrastructure decision. For defense-adjacent manufacturers with CMMC obligations, this is not optional. Shelorve designs these requirements into the baseline architecture of every manufacturing engagement.
What We Deliver

What we deliver for Manufacturing organizations

Industrial IoT & Predictive Maintenance

Real-time machine telemetry pipelines on AWS Kinesis, ML models for failure prediction on SageMaker, and maintenance scheduling integrated with ERP — built for operations teams who need to trust and act on what the model tells them, not just data scientists who need to evaluate it.

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SAP and Legacy ERP Modernization Add TM to codesight

CodeSight-led modernisation of SAP and legacy MES environments — production schedules maintained throughout every phase, undocumented integrations mapped before any work begins, and zero big-bang cutovers.

Explore Legacy Transformation →
AWS Cloud for Manufacturing

Cloud data platforms connecting shop floor telemetry to enterprise analytics — IoT Greengrass for edge processing, Kinesis for real-time ingestion, S3 data lake, Redshift for analytics, and CloudWatch for operational monitoring.

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Salesforce for Dealer Networks

Sales Cloud and Experience Cloud for dealer network management and distribution portals, Service Cloud for field service management — all connected to ERP via MuleSoft so Salesforce holds real inventory and order data.

Explore Salesforce →
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Production interruptions during legacy ERP and MES modernization
Real-time
Shop floor telemetry connected to enterprise analytics
Predicted
Equipment failure identified before it becomes unplanned downtime
Manufacturing · Common Questions

What manufacturing leaders ask us before they engage

It is embedded in every Shelorve engagement. Test strategy, automation, CI/CD integration, and defect pattern analysis are not optional add-ons — they are part of how every program is delivered. There is no version of a Shelorve engagement that does not include Quality Engineering.
The toolset is selected based on the technology stack. For AWS serverless: Jest, Postman/Newman, AWS CodePipeline, and Locust for performance. For Salesforce: Apex tests and Provar. For data pipelines: Great Expectations or dbt tests. For front-end systems: Playwright or Cypress. The toolset is documented at engagement start and handed over with the system.
Legacy systems often have no existing test coverage — and the code is frequently not testable in its current state. Shelorve builds the regression suite as part of the engagement, starting with the highest-risk business processes identified during the discovery phase. Code is also refactored for testability as part of the migration, so the modernized system is inherently more maintainable than what it replaced.
Test coverage is prioritized by business risk and defect history. We identify the integrations and code paths that carry the most risk, and we use defect pattern analysis on available incident history to identify the areas of the codebase that have failed most often. High-risk, high-defect areas get full coverage. Low-risk, stable areas get lighter coverage. The result is a test suite that is proportionate and maintainable rather than exhaustive and expensive.
Yes. Shelorve can assess an existing test suite, identify gaps and inefficiencies, and bring it to a standard that provides genuine confidence in releases. This often involves removing tests that are testing the wrong things, consolidating overlapping tests, and adding integration and performance coverage that is typically absent from inherited suites.
Performance testing is designed into the program from the start — not added before go-live when the architecture can no longer change. Load profiles are built from real usage data, historical transaction volumes, and anticipated peak scenarios. Shelorve runs load tests against each environment as it is promoted, so performance regressions are caught early. Go-live is never the first time the system has run under real load.
Manufacturing transformation

starts with understanding
what the plant floor is actually running.

Tell us what you are trying to solve. We understand OT/IT integration, ERP legacy debt, and what it takes to connect shop floor telemetry to enterprise decision-making — without stopping production to do it.

Talk to a Principal → All Industries