Acquisition
SolvingAI: Strategic Due Diligence That Prevented a Costly Misalignment
An AI-powered digital adoption platform needed independent analysis of an acquisition opportunity before committing capital and resources.
SolvingAI is building intelligent in-app guidance systems for enterprise software, helping users navigate complex ERP platforms. When they identified an acquisition target—an established ERP training company with extensive content libraries—the opportunity seemed compelling. The target offered two products: a training platform with sandbox environments and an AI-augmented in-app guidance overlay. On paper, acquiring these assets could accelerate SolvingAI's product roadmap significantly.
Challenge
SolvingAI needed to determine whether acquiring this business made strategic sense, but lacked visibility into critical details. The target's financials showed stagnating revenue, yet the company had valuable partnerships and extensive content. Without product-level profitability data or customer-level metrics, SolvingAI couldn't assess whether they were looking at a turnaround opportunity or a strategic asset play. More fundamentally, they needed to understand whether this acquisition aligned with their capabilities or if it would transform them into something entirely different.
What We Did
We worked together over three months to conduct comprehensive due diligence across two scenarios: full business acquisition and selective asset acquisition. We performed detailed P&L analysis to understand the economics, built revenue models to project future performance, and assessed the operational complexity of integrating a 45-person organization. We analyzed each product line independently despite missing financial breakouts, evaluated the strategic fit of the training business (outside SolvingAI's core competency) versus the in-app guidance platform (built on competitor technology requiring complete replacement), and identified the critical gap: SolvingAI hadn't yet built the proprietary technology needed to replace the competitor dependency. We also explored the asset acquisition path, evaluating whether documentation libraries and customer environments could accelerate SolvingAI's AI agent development without inheriting operational complexity.
Outcome
SolvingAI gained clarity on what they were really considering: not a startup acquisition, but a private equity-style operational turnaround that would fundamentally transform their business model. Our analysis revealed that proceeding would mean simultaneously building unproven replacement technology, managing 45 employees, maintaining products outside their expertise, and reversing revenue decline. We recommended they walk away from the acquisition at this time and instead focus on building their proprietary platform first, then revisiting the opportunity with proven technology and adequate capital. The recommendation included an alternative path: develop their DAP platform independently over 12-18 months, prove it works with initial customers, then consider selective asset acquisition to capture valuable content libraries without operational complexity. SolvingAI now has a clear strategic framework for acquisition decisions and understands the difference between opportunistic deals and strategic fit.
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