A guide by SevenLab
Custom AI software makes sense when a valuable requirement cannot be met adequately through an existing product or configuration. It is not automatically the faster or cheaper route. Use this guide to compare buying, extending and building, and to prepare a meaningful discussion with SevenLab about an AI application or platform.
Identify the requirement that justifies custom software
List the tasks users must complete, the systems they already use and the constraints a solution must respect. Test standard software against those requirements before treating custom development as the default. Configuration or an extension may solve the problem with less ownership burden. Custom development becomes more credible when a distinctive workflow, permission model or interface is materially important.
Illustrative scenario: a field-service company wants staff to search manuals, prepare a report and send it for review from one interface. A generic assistant may handle part of the search task but leave reporting fragmented. The buying decision should turn on whether a configured product can meet the complete workflow, not whether a custom demo looks more impressive.
- Separate essential workflow requirements from preferences.
- Test existing products with the same representative user tasks.
- Document the unmet requirement that would justify custom development.
Use a proof of concept to answer a difficult question
A proof of concept should test the assumption most likely to invalidate the project. That may be answer quality on technical documents, extraction from poor scans or access to an essential data source. Define the evaluation material and decision rule before development starts. A prototype can demonstrate interaction design without proving accuracy, security or operational readiness.
Illustrative scenario: an internal team wants a multilingual knowledge app but is unsure whether the source material supports useful answers. The first experiment should test representative questions and source gaps, not build a complete dashboard. If the evidence is weak, the next step may be improving documentation or narrowing the scope rather than adding more application features.
- Write one falsifiable question for the proof of concept.
- Reserve evaluation examples that are not used to tune the prototype.
- Agree the conditions for proceeding, changing scope or stopping.
Plan the application around its users and failure modes
Production requirements extend beyond the model. Specify sign-in, permissions, data retention, source handling, error recovery and human review. Determine where the AI output is advice and where it affects a business record. Ask how the interface would communicate uncertainty and let users correct mistakes. These requirements need explicit agreement rather than being inferred from a working prototype.
For a shared platform, also assess separation between user groups, administrative access and how changes reach different teams. Investigate each required integration rather than assuming availability. Deployment location, model providers and data handling should be reviewed against your organisational requirements. Appropriate technical and legal review may be necessary; a custom build does not itself guarantee compliance.
- Define roles, data boundaries and approval points before release.
- Test complete user tasks, including incorrect output and service failures.
- Confirm integration feasibility and the proposed data-handling architecture.
Compare the whole lifecycle and agree an exit route
Custom software needs ongoing decisions about hosting, model changes, dependencies, monitoring and support. Compare those responsibilities with the limitations and subscription dependencies of a standard product. Ask who owns custom deliverables, which components remain subject to third-party licences and how data and configuration can be exported. Avoid treating development completion as the end of ownership cost.
Use the existing pricing page to begin the budget discussion, then request a proposal tied to scope and acceptance. A fixed-price stage can be assessed once deliverables and exclusions are sufficiently clear; do not assume one is available for every uncertainty. Agree maintenance boundaries and handover materials so that another team can understand the application if responsibilities change.
- Compare implementation, operation, maintenance and exit effort for each option.
- Record code rights, third-party dependencies and export requirements.
- Review pricing and request explicit acceptance, support and handover terms.