Illustrative scenario
Testing an acquisition target’s platform and AI claims before signing
An investor’s deal team weighing the acquisition of a vertical software company whose growth plan depends on larger customers and new AI features.
- Challenge
- Management says the platform will scale to larger customers and that its AI features are hard to copy. The deal team cannot tell how far the code, the hosting setup and the target’s data rights support those claims, and the timetable leaves no room for surprises after signing.
- Approach
- 1Turn the investment thesis into specific technical questions, agreed with the deal team before the review starts
- 2Review repositories, cloud accounts and incident history with read-only access, and scan for code quality, vulnerable dependencies and license obligations
- 3Interview the target’s technical leaders about architecture, delivery practices and who holds critical knowledge
- 4Trace how each AI feature works: which models it calls, which customer data it uses under what contract terms, and what each request costs
- 5Rate findings by severity with remediation ranges, raise deal-relevant issues as they surface, and draft a post-close plan
- Outcome
- The deal team negotiates knowing which claims hold up and which risks need fixing early in ownership. The post-close plan gives the new owners a prioritized first phase that the target’s engineers, our teams or another vendor can deliver.
Services involved
