Problems that appear in systems already in operation.

Problem

Stock, orders, documents and statuses drift apart across systems. The team fixes records by hand and cannot tell which system is correct.

What we change

We define which system owns orders, stock and statuses. We connect APIs or file exchanges, then add validation, retries and alerts.

After the change

The team makes fewer manual corrections. If synchronization stops, the responsible person receives an alert showing where the error occurred.

Problem

Procedures and decisions are scattered across documents, email and business systems. The answer depends on who happens to be available.

What we change

We organize the sources, connect them to search and show which document supports each answer. Questions without a reliable answer go to the right person.

After the change

The team finds answers faster and can verify the source document.

Problem

Documents, requests or case descriptions must be read, classified and turned into a proposed next step.

What we change

The model extracts the required data and prepares a proposal. The system checks agreed rules, and a person approves the result where an error would matter.

After the change

Each case takes less time to prepare, and the system records who approved the result and why.

Problem

The team relies on the system every day but cannot tell which dependencies block development or where modernization should begin.

What we change

We review architecture, code, integrations, deployment and maintenance. We turn the findings into a plan ordered by risk and operational impact.

After the change

The team knows what to fix first, what can wait and which parts do not need to change.

Problem

The main application handles most of the work, but it lacks a specific role, approval, status or exception path.

What we change

We add the missing module and connect it to the current data, permissions and deployment process.

After the change

The team gets the required capability without replacing the platform or maintaining another copy of the same data.

Problem

ERP, CRM and the data warehouse calculate statuses, corrections or dates differently, so departments work from conflicting numbers.

What we change

We define how statuses, corrections and dates are calculated and which system owns each value. We add reconciliation and alerts for missing or delayed records.

After the change

Reports use the same rules. When numbers differ, the team can see which system caused the discrepancy and who should investigate it.

Problem

People use coding agents and AI tools in different ways, so good results are hard to repeat and changes are hard to review.

What we change

We work on tasks close to the team's actual work: code discovery, planning, implementation, tests and review. We also define when an agent requires human review.

After the change

The team has shared rules for using AI and can verify the result in code, tests and documentation.

Problem

In a large migration, some mappings are prepared by hand and data errors may surface only when the new system goes live.

What we change

We keep migration rules in the repository, run trial migrations and compare results. Exceptions and rejected records require explicit approval.

After the change

Before the switch, the team knows what moved, what was rejected and who approved each exception.