AI Vendor Due Diligence

Private equity firms evaluating portfolio company marketing technology investments, enterprise procurement teams assessing vendor claims, CFOs reviewing significant AI marketing proposals, and board members conducting fiduciary oversight of technology spending.

This service makes sense when the proposed vendor investment exceeds $50K annually or when the technology decision could lock your organization into multi-year commitments. The due diligence protects capital and ensures genuine AI capability rather than rebranded legacy automation.

We conduct forensic technology evaluation: researching the vendor's actual development timeline (was this built pre- or post-ChatGPT?), auditing their technical architecture documentation, analyzing performance data patterns to identify human intervention vs. systematic AI improvement, and evaluating their strategic completeness (do they address search behavior evolution, platform AI features, cross-channel implications, or just content generation?).

We also perform cost-benefit analysis factoring all implementation fees, calculate true ROI net of vendor costs, and compare against building genuine AI capabilities internally or with alternative vendors.

Timeline verification is critical. We research when the technology was actually developed—platforms built 18+ months before ChatGPT's launch cannot legitimately claim "generative AI" capabilities. We examine their technical documentation, API integrations, and whether they're using current AI models (GPT-4, Claude, Gemini) or just automating legacy processes.

Performance patterns reveal the truth: genuine AI shows consistent, systematic improvement. Human intervention disguised as "AI optimization" shows wild variance, manual adjustment patterns, and performance that correlates with business hours rather than continuous algorithmic learning.

AI content generation is the surface layer—using ChatGPT or similar tools to write ad copy, blog posts, or creative variations. It's valuable but limited. Complete AI strategy addresses fundamental market transformation: how search behavior changes when people use AI assistants, how to leverage platform AI features (Google's AI Overviews, Performance Max, Meta's AI placements), how to use LLMs for real-time analytics and decision-making, and how to restructure budgets across paid, organic, and emerging channels.

Most vendors stop at content generation and call it "AI transformation." We evaluate whether they're addressing the complete strategic opportunity or just providing rebranded content tools at premium pricing.

A standard AI vendor assessment takes 2-3 weeks from engagement through final report delivery. This includes technology timeline research, vendor documentation review, performance data audit, strategic completeness evaluation, and cost-benefit analysis.

Complex assessments involving multiple vendors, extensive performance data, or detailed competitive analysis can extend to 4-5 weeks. We provide preliminary findings within the first week so time-sensitive decisions can proceed with initial intelligence while we complete comprehensive evaluation.

Vendor resistance to technical transparency is itself valuable intelligence. Legitimate AI platforms should be able to document their technology architecture, model integrations, and development timeline. Refusal often indicates they're protecting rebranded legacy systems or manual processes disguised as automation.

We proceed with external research—development timeline verification, patent searches, technical blog analysis, former employee LinkedIn profiles showing pre-generative work, and performance pattern analysis that reveals human intervention. Lack of vendor cooperation doesn't prevent assessment; it just changes our methodology.

Our core expertise is marketing AI—advertising optimization, search evolution, analytics automation, content generation, and customer targeting. We understand both the marketing context and the underlying AI technology, which is why our assessments are effective.

For AI vendors in adjacent spaces (sales automation, customer service, data analytics), we can often provide valuable evaluation if there's overlap with marketing intelligence. For completely different domains (healthcare AI, manufacturing AI), we'd recommend specialists in those verticals who understand the domain-specific requirements.

You receive a comprehensive report documenting our findings—technology timeline verification, strategic completeness evaluation, performance analysis, cost-benefit assessment, and clear recommendations. The report is designed for investment committee or board-level review with executive summaries and detailed technical appendices.

We also provide a consultation session to walk through findings, answer questions, and discuss implementation alternatives. Many clients use our assessment to negotiate better vendor terms, identify superior alternatives, or build business cases for internal AI development. The deliverable is yours to use however serves your strategic interests.

We do both. The due diligence service is independent assessment—we have no financial incentive to recommend any particular vendor or approach. We're paid for analysis, not implementation.

However, if our assessment reveals that building internal AI capabilities or implementing alternative solutions would be more effective than the vendor being evaluated, we can provide implementation services. This creates natural alignment: we only recommend what genuinely serves your strategic interests, and you have the option (not obligation) to engage us for execution.