The product claim needs testing
The business case depends on scale, AI capability, defensibility, integration, or speed that has not been independently evidenced.
Technical due diligence
Know what the technology can support
before the deal depends on it.
Independent technical diligence that connects product claims, architecture, delivery capability, security, operations, and technical debt to the commercial decision.
Reviewed and led personally by Alan Son.
20+years in production systems
AMPDco-founder and CTO
CarBuddy AICTO
Portableyour code and data stay yours
The evidence gap
A code review alone cannot explain whether the technology supports the deal.
The relevant risk sits across product fit, system design, data, security, team capability, delivery history, operations, ownership, and the cost of the next stage.
Technical debt is described too broadly
Stakeholders know debt exists, but not which liabilities change cost, timing, security, or strategic options.
The team is part of the asset
The decision depends on whether knowledge, leadership, delivery capability, and ownership can survive the transaction.
What changes
A decision-ready view of capability, liability, and next-stage cost.
Findings are prioritised by commercial impact and supported by evidence, with uncertainty made explicit rather than hidden in a generic score.
- 01 Product and architecture capability assessment
- 02 Security, data, operational, and ownership risks
- 03 Team and delivery capability review
- 04 Prioritised findings with remediation implications
How we work
Diligence shaped around the decision, not a checklist.
I agree the investment thesis, transaction questions, access, and reporting needs first. The review then targets the evidence most likely to change the decision or its terms.
Frame
Define the decision, claims, material risks, and evidence standard.
Inspect
Review product, code, architecture, data, operations, security, and team evidence.
Challenge
Test material claims and expose dependencies, uncertainty, and next-stage cost.
Report
Deliver concise findings, risk priority, and decision implications.
Operator proof
Advice from someone accountable for live AI products.
I do this work while building and operating commercial products. The recommendations have to survive real users, real constraints, and real production systems.
01 / AMPDCo-founder and CTO
AI citation intelligence across the discovery journey.
Product strategy, data systems, platform architecture, and production delivery.
Visit AMPD02 / CarBuddy AICTO
Conversational AI connected to dealership operations.
AI workflows, vertical SaaS, customer communication, and reliable commercial systems.
Visit CarBuddy AIUseful questions
Clear boundaries make better engagements.
Who is the diligence for?
The work supports investors, acquirers, boards, lenders, founders preparing for a transaction, and leadership teams making a material partnership decision.
Can you work under a short transaction timeline?
Yes. Scope and evidence depth are agreed against the time available, with limitations and uncertainty stated clearly.
Can you support remediation after the review?
Yes, when independence requirements allow it. I can advise the company, support a 100-day plan, or lead focused remediation.
Start with the current truth
What would a useful first conversation need to resolve?
Share the situation, the pressure, and what has already been tried. I will review it personally and tell you plainly whether AlanOps is the right fit.
- No generic sales sequence
- No obligation to commission delivery
- A direct response from Alan