Orders need too much manual follow-up
Sales, planning, and shipping re-enter information or chase updates across separate systems.
Software for growing manufacturers
Expand your CRM & ERP.
Connect production to AI agents.
Take your e-commerce to the next level.
Modernize legacy systems to support new capabilities, connected operations, and easier online ordering. Our engineers use AI to uncover existing business rules and deliver improvements in manageable stages, with your team validating each change.
Connect existing systemsUpgrade aging technologyMigrate applications & dataTake over & stabilize
Start with the operational bottleneck
Where is your software holding the business back?
Your ERP may still do its core job. The friction often sits between departments, inside a custom application, or in a process only a few people understand.
Material and production status arrive too late
Planners rely on spreadsheets because purchasing, inventory, and shop-floor records do not agree.
Every change depends on one person
Customer exceptions, quality checks, and reporting rules are buried in code or undocumented workarounds.
The technology is getting harder to support
Aging frameworks, fragile integrations, and slow applications make routine improvements expensive.
Recover the business knowledge
Make the rules inside your software visible.
Our engineers use AI to analyze code, databases, interfaces, and configuration, then connect the findings in a business knowledge graph: a map of how your workflows, rules, and data depend on each other.
- 01OrderProduct revision
Customer terms - 02MaterialsBill of materials
Stock allocation - 03ProductionRouting & capacity
Work-order status - 04QualityInspection results
Release approval - 05ShipmentLot traceability
Shipping documents
A rule to confirm
A quality hold prevents shipment until an authorized person releases it.
Trace the evidence
Application rule → quality record → shipping integration → observed behavior
Traceable to the systemChecked against actual behaviorConfirmed with business owners
A shared basis for better decisions
You review a prepared map and focused questions with our team. Together, we identify rules to preserve, outdated behavior to change, and manual work the system does not capture. The map then guides development, testing, and future AI opportunities.
From shared understanding to working software
Improve one business priority at a time.
Each stage has a defined outcome for your team to review. AI accelerates analysis and implementation; engineers remain responsible for the design, verification, and release.
- 01
Agree on what matters first
Rank improvements by operational value, dependencies, and risk. Decide what to retain, connect, upgrade, or replace. Separate existing rules from intentional business changes.
You review: A phased roadmap, scope, responsibilities, and an estimate for the first stage.
- 02
Put working changes in your hands sooner
Engineers use AI to build prototypes and small, reviewable increments. Your team sees the workflow early and provides feedback before the change expands.
You review: Working software against agreed acceptance criteria.
- 03
Test the business outcome
Build tests from confirmed rules from the start. Cover normal work, exceptions, permissions, and downstream effects, such as partial shipments or a rejected material lot.
You review: Test evidence, open issues, and comparisons with current behavior.
- 04
Migrate in controlled stages
Use AI to accelerate data mapping, conversion scripts, and reconciliation. Migration tools move and synchronize records. Validate old and new results in parallel where feasible.
You review: Reconciled data, cutover readiness, and a recovery plan.
- 05
Keep improving after release
Use automated delivery practices, or DevOps, for repeatable builds, tests, and deployments. Monitor live behavior and plan application rollback and data recovery together.
You review: Release records, operating guidance, support ownership, and the next priorities.
Protect daily operations
A working demo is one step. Readiness to switch is another.
Plan the transition around shifts, production schedules, shipping commitments, and financial close. Agree on the evidence and operating conditions for each release.
Talk through your operating constraintsDo the critical workflows still work?
Compare approved scenarios across systems, including exceptions and connected equipment or applications.
Do the records and totals reconcile?
Check quantities, units, relationships, historical records, and business totals—not just record counts.
Which system can take action?
Define the authoritative source and writing permissions to prevent duplicate shipments, invoices, or inventory movements.
What happens if a release needs to stop?
Set monitoring, stop conditions, and recovery steps that account for transactions already processed.
Relevant delivery experience
Modernization grounded in operational work.
Explore how Shinetech teams have handled connected equipment, historical data, and departmental systems.
Recycling operations
Preserve the transaction chain while improving the platform.
Incremental modernization addressed performance and integration across weighing, identification, pricing, and business systems.
Read the recycling case
Automotive manufacturing
Move engine performance data to a new application foundation.
A C++ to C# migration combined pre-migration analysis with manual scenarios and repeatable automated testing.
Read the data migration case
Textile manufacturing
Connect material flow across independent databases.
A shared integration layer connected departmental workflows while preserving existing database structures.
Read the supply chain caseCase illustrations show the workflows described.
An optional next step
Put AI to work where it can improve the business.
The business map helps identify work that involves repeated searching, reading, or coordination. Our forward deployed engineers work with your operations team to select a focused pilot and connect it to the right systems.
Find trusted answers
Enterprise knowledge base
Help staff find approved procedures, product specifications, and troubleshooting guidance. Retrieval-augmented generation (RAG) grounds answers in company sources, with citations and access permissions.
Evaluate: Answer accuracy and time spent finding information.
Explore enterprise knowledge basesReduce document handling
AI inside an existing workflow
Extract details from supplier documents, summarize quality reports, or prepare responses to customer requests. Route uncertain results and required decisions to the right person.
Evaluate: Handling time, extraction accuracy, and correction effort.
Explore workflow automationCoordinate across systems
A custom business agent
Let an agent gather order, inventory, and delivery information, flag an exception, and prepare the next action. Define which actions it may execute and which need human approval.
Evaluate: Task completion, exception resolution, and review effort.
Work with an embedded AI engineerYour business decides where AI belongs.
AI-assisted engineering does not require AI in your live system. Keep fixed calculations and mandatory controls in conventional software. Start an AI pilot when the data, interfaces, and business case are ready—even while other modernization work continues.
Questions before you start
A clear scope. A practical commitment.
Bring your operational priorities. We will help turn them into the right technical questions.
Do we need to replace our entire ERP?
Not necessarily. We assess which parts can stay, which need an upgrade, and where an integration or a focused replacement will solve the problem. The roadmap follows your operational priorities, existing investments, and support requirements.
Can you work with a system that has no documentation?
Yes. Our engineers use AI-assisted analysis of available code, databases, interfaces, and configuration to reconstruct a business knowledge graph. We validate it against system behavior and discussions with your team, including manual workarounds that code alone cannot explain.
How much time will our operations team need to contribute?
We agree on the people and review points during scoping. Your team helps confirm critical rules, choose priorities, and review working increments. We bring a prepared business map, specific questions, and test results so each discussion has a clear purpose.
Can the old and new systems run in parallel?
Where the architecture allows it, we compare the same business scenarios in both systems before switching a workflow. We define which system can write records and trigger actions, how changes are synchronized, and what must pass before cutover. Any required downtime is planned with your team.
How do you protect our source code and production data when using AI?
We agree on permitted tools, model access, data handling, and retention requirements before analysis begins. Access is limited to the approved scope. Engineers review generated changes, and confidential records are minimized or masked where appropriate.
Does modernization mean putting AI in our production workflows?
No. Using AI to help engineers deliver the project is separate from adding AI to your business. You can modernize without introducing a runtime AI model. If you choose a business AI pilot, we agree on its purpose, data access, human approvals, and measures of success.
How do you estimate cost and timeline?
We start with system access, business priorities, integrations, data condition, and operational constraints. Discovery produces a phased scope, assumptions, dependencies, and an estimate for the first delivery stage. Later stages are refined as the team verifies the system and your priorities.
Your first conversation
Which workflow needs to work better?
Tell us where work slows down, which systems are involved, and what must keep running. We will discuss the initial assessment, the people to involve, and a sensible first delivery scope.
Useful context: your main bottleneck, current applications, and any upcoming deadline.
Get in touch
Ready to build software that fits your business?
Tell us what you need to build, modernize, automate, or augment with AI. We can start with a focused discussion or a no-risk 1-week trial.
“A fantastic company to work with.” After the initial rapid development project, American Shipping Co. kept two Shinetech developers embedded for nearly four years, supporting internal and external tools and new AI initiatives.
CEO, American Shipping Co. - 5-star Google Review