AI Re-underwriting / 02 · Ownership economics · For current owners
AI Re-underwriting assesses whether advancing AI models and new entrants threaten your software's position—and what a credible response would require. We combine code-level evidence with an assessment of current model capabilities and competing implementations to identify what remains defensible, what is exposed to substitution, and where reengineering could strengthen the investment case.
You receive a technical judgment and a clear path: Hold & Defend, Reengineer & Reprice, or Exit & Preserve Value.
Delivery begins with complete access to the agreed software, artifacts, and product context.
The question
The product may do its job today. The question is whether its advantage survives a change in what models can do and how competitors can build.
We examine the software against its intended job and the owner's investment thesis. Which capabilities are difficult to reproduce? Which are becoming readily available? Where could a new implementation change the cost, performance, or completeness of the solution?
Current model capabilities and demonstrated competing implementations are assessed as evidence. Forward scenarios identify the capabilities that would have to emerge to change the judgment.
The paths
The assessed substitution threats leave meaningful technical advantages intact. The assessment identifies what the owner can substantiate to the next buyer and what the product needs to preserve.
Make the advantage underwritable.The assessment identifies the smallest product change capable of materially improving the response to the threat. It establishes what needs to be built, the effort involved, and the revenue, margin, defensibility, or exit assumptions the change could affect.
Build the capability that changes the case.The substitution threat is material, and the assessed response offers insufficient improvement in technical position to justify the proposed work. The owner receives a clear basis to consider an exit before that exposure deepens.
Preserve value while options remain.Each path identifies the evidence, assumptions, and unresolved questions that matter to the owner's decision.
The assessment
The assessment brings five dimensions together to show what to protect, what to rebuild, and whether the expected technical improvement supports further investment.
Architecture, security, reliability, scalability, maintainability, dependencies, change history, and team concentration, measured by the platform.
Which jobs the product performs, how far current models can perform those jobs, and which plausible capability advances would threaten its role.
Where a competitor using newer tools can reproduce the solution, improve its performance, or change the cost of delivering it.
The specialized functionality, data dependencies, integrations, architecture, and operating requirements that make substitution difficult.
The feasibility and effort of preserving or rebuilding an advantage, tied to the specific value assumptions the owner wants to improve.
Scope
AI Re-underwriting is a complete, fixed-fee engagement. Two of its three verdicts — Hold & Defend and Exit & Preserve Value — conclude with the assessment.
Reengineer & Reprice lays out the investment case for product change: the proposed capabilities, an outline of the scope of work, an initial estimate of the required effort, and the potential effect on defensibility and exit value.
If you commission AI Reengineering from Big Lever AI, we scope a separate engagement around the smallest intervention capable of improving the position. Your $30,000 assessment fee is credited in full toward that work.
The required intervention determines the scope: a focused change, a new capability, or a successor product.
Named-asset thesis
We approach a named company with an outside-in view of the technical threat and the opportunity worth testing. The engagement tests that thesis against the software itself and the job it needs to perform.
Talk to a PrincipalThe platform
Our AI analysis platform establishes software condition and the evidence behind it. We assess those findings alongside the product's intended job, current model capabilities, competing implementations, and the owner's investment thesis. That connects technical exposure to a decision about defending, reengineering, or exiting the asset.
AI Re-underwriting / 02
