START WITH YOUR WORK
Legacy Modernization Partner for Software Agencies
Scope legacy assessments and migration work alongside your agency. Define confidentiality, code handover and acceptance before delivery.
When should an agency bring in a technical partner?
Taking on an aging application requires a clear scope before extra capacity becomes useful. We shape the engagement around your client relationship and your team’s existing development process.
- New projects fill the schedule. Discovery and maintenance of an older application have no allocated time.
- The estimate has too many unknowns. Code condition and dependencies make dates and fees difficult to commit to before assessment.
- Knowledge stayed with a previous developer. It is unclear which business rule a small request might affect.
- Responsibility after handover is vague. Defect correction, operations and new requests become mixed together.
What belongs in a white-label delivery agreement?
A white-label subcontracting arrangement specifies who communicates with the client and how deliverables are presented. Before code or data is shared, we discuss a non-disclosure agreement, access boundaries, intellectual property and the use of third-party tools. Publishing a client name, logo or result requires separate explicit approval.
Capacity and dates are agreed in writing after discovery. The work can be a bounded module, review or migration step. Delivery time, review time and dependencies between teams belong in one plan.
What happens between discovery and code handover?
- Define the engagement: client objectives, existing contractual boundaries, confidentiality and communication.
- Assess the work: required access, dependencies, unknowns and acceptance criteria for the first package.
- Deliver for review: version-controlled changes, test results and review notes, with progress shared at an agreed cadence.
- Hand over: setup and operating documentation, outstanding work and the contract’s support or warranty provisions.
Hours alone do not show whether the work is moving forward. Accepted work packages, open blockers, review waiting time and completed handover documents can be tracked together. These are proposed measures for an engagement, not claims about past delivery performance.
Where a work package can start
A Legacy Health Check can support discovery before an estimate. Application modernization can focus on a separable module. Integration and AI can focus on a specific flow between systems. Implementation scope is not finalized before reviewing the code and completing a small validation exercise.
The PHP, frontend and desktop pages describe assessment options. The client’s business case can distinguish maintenance cost, continuity and handover and performance.
From the lab
Unindexed query → Same query + composite index
Database optimization: queries and indexes
200,000 orders summarized: 1.13 s → 7.19 ms. Synthetic lab; median of 10 runs. Open code and raw data.
200,000 orders summarized
↓ 99.4%Lower is better · Median of 10 runs
Measurement method →Scan the list for every row → Dictionary lookup by product code
.NET bulk import: faster catalog lookups
50,000 catalog import rows: 708.22 ms → 1.51 ms. Synthetic lab; median of 10 runs. Open code and raw data.
50,000 catalog import rows
↓ 99.8%Lower is better · Median of 10 runs
Measurement method →Render every matching row → Render the visible window
Frontend optimization: a 50,000-invoice list
50,000 invoices filtered and listed: 1.39 s → 16.5 ms. Synthetic lab; median of 10 runs. Open code and raw data.
50,000 invoices filtered and listed
↓ 98.8%Lower is better · Median of 10 runs
Measurement method →Java 8 · sequential calls → Java 25 · virtual threads
Java 8 → 25: parallelizing an order integration
256 orders completed: 2.95 s → 380.91 ms. Synthetic lab; median of 10 runs. Open code and raw data.
256 orders completed
↓ 87.1%Lower is better · Median of 10 runs
Measurement method →Unindexed month-end report → Same report + covering index
Month-end reports across five million records
5,000,000 orders summarized: 1.22 min → 175.5 ms. Synthetic lab; median of 10 runs. Open code and raw data.
5,000,000 orders summarized
↓ 99.8%Lower is better · Median of 10 runs
Measurement method →Rescan for every customer → Aggregate in one pass
PHP report optimization: one-pass aggregation
200,000 orders summarized: 1.27 s → 8.49 ms. Synthetic lab; median of 10 runs. Open code and raw data.
200,000 orders summarized
↓ 99.3%Lower is better · Median of 10 runs
Measurement method →Corretto 8u432 → Corretto 25.0.3
Java 8 → 25: one order report, two runtimes
The same bytecode reports over 1 million in-memory orders in 1.891 ms → 1.886 ms. A synthetic runtime study across seven data sizes and 440 real JVM runs.
In-memory report over 1 million orders
↓ 0.3%Lower is better · Median of 10 runs
Measurement method →