Clarivia supports mid-market Private Equity teams with a thesis-aligned deep dive across Product, R&D, AI readiness, Go-to-Market, Sales, Marketing, and Operations. The goal is simple: reduce “unknowns” that could break a deal post-close and convert what we learn into a practical value-creation plan that management can execute from Day 1.
- Cross-functional operator depth across product, engineering, go-to-market, and operating cadence
- Diligence that ties facts to value creation: what to fix, what to invest in, what to sequence first
- Outputs designed for investment committees: clear assumptions, evidence, and decision implications
What this diligence is (and is not)
This is not a narrow technical audit. Clarivia’s due diligence is an operator-led assessment of whether the company can deliver the investment thesis with the product it has, the R&D organization it runs, and the go-to-market engine it depends on. We look for points where the system breaks under scale: product decisions that do not align with customer reality, R&D throughput that cannot sustain roadmap commitments, AI claims that do not withstand scrutiny, or GTM execution that appears healthy on a forecast but weak in underlying mechanics.
The end product is not just a findings deck. It is a value-creation plan that translates facts into sequencing, resource implications, and an operating cadence that management can execute immediately after close.
The Clarivia diligence focus
Product and value proposition truth
We assess whether the product is genuinely positioned to win in the segments that matter to your thesis. That means pressure-testing the ICP, the differentiation story, and the roadmap credibility. In many deals, the hidden risk is not “bad technology.” It is a mismatch between what the product is optimized for and what the go-to-market is selling, or a roadmap that cannot be executed with the current throughput. Clarivia surfaces those mismatches early, with evidence.
R&D execution capacity (delivery reality)
R&D is evaluated as a delivery system, not as an org chart. We examine how priorities are set, how predictable delivery is, and where velocity is lost. This is where PE partners often need the clearest answer: is the organization capable of delivering what the thesis requires, and if not, what will it take (time, talent, changes in operating model) to get there. The outcome is a grounded view of execution risk and remediation effort.
AI readiness and differentiation (when “AI” is part of the thesis)
If “AI” is in the deal narrative, we separate durable advantage from messaging. We assess data readiness, governance, security, and privacy constraints, and whether AI creates measurable leverage in the product or the operating model. The point is not to debate buzzwords. The point is to answer whether AI is likely to improve retention, pricing power, or efficiency in a way that survives a holding period.
Go-to-market system coherence
Many software deals fail to meet the plan because the GTM system is inconsistent. Clarivia evaluates whether positioning, marketing, and sales execution reinforce one another and whether pipeline quality aligns with the forecast story. We look for the “silent killers”: dependency on a narrow channel, lead flow that converts for the wrong reasons, or a sales motion that is a misfit for the segment.
Sales engine performance
Sales diligence is about repeatability. We assess whether the coverage model, capacity, and sales motion can scale without breaking unit economics. We also assess the forecast’s reliability and the pipeline’s quality, with attention to common indicators such as concentration risk, discounting patterns, and slippage dynamics. This is typically where we determine whether growth is structural or being propped up by heroics.
Marketing effectiveness (not activity)
Marketing is assessed as a pipeline and narrative system, not an activity list. We look at whether the company can consistently generate qualified demand, whether messaging is anchored in real differentiation, and whether marketing supports retention and expansion. The output is an understanding of what is actually working, what is noise, and where targeted changes can create disproportionate returns.
Operations and operating cadence
Finally, we evaluate operational reliability: how decisions are made, how accountability works, and whether the company has a usable metric system. Many post-close disappointments are execution failures, not strategy failures. Clarivia’s diligence identifies where decision velocity and cross-functional alignment will break under pressure, and what cadence is required to run the plan.
The Clarivia diligence approach
- Thesis alignment. We start by clarifying what must be true for the deal to work, and what “good” looks like under your investment thesis.
- Focused operator deep dive. We run targeted interviews and artifact reviews across the seven focus areas, triangulating signals rather than relying on single-source narratives.
- Translate findings into deal implications. We convert observations into investment consequences: risk severity, timing, cost, and organizational constraints.
- Value creation plan. We deliver a first-100-days plan plus a 12-month roadmap with sequencing, ownership, and an operating cadence.
What you get (deliverables)
You receive a diligence package designed to provide investment committee clarity and support post-close execution. It includes deal-critical risks and constraints, evidence-based upside levers, and a value-creation plan that management can execute. Where relevant, we make explicit the “if/then” logic: if the thesis depends on X, then the company must be able to do Y, and today we see Z, which implies these actions and this timeline.
Typical outputs include:
- A risk and constraint map (severity, likelihood, mitigation path)
- A value creation plan (first 100 days + 12 months)
- A recommended KPI set and operating cadence to run the plan
- Optional modules for carve-outs, integration planning, or post-close execution support
Engagement models
- Rapid screen: thesis pressure-test, key risks, and what to verify next.
- Full diligence: integrated review across Product, R&D, AI, GTM, Sales, Marketing, and Operations.
- Post-close sprint: convert diligence into operating reality with management through cadence, sequencing, and unblockers.
Why Gérard
Gérard brings cross-functional operator depth that maps directly to what drives value in software deals: product decisions, R&D throughput, AI realism, GTM mechanics, and execution cadence. The work is designed to help sponsors underwrite with confidence and enter Day 1 with a realistic, sequenced, and measurable plan. (Gérard’s LinkedIn Profile)
Request a Diligence Fit Check
Share your deal thesis and timeline. We’ll confirm scope, access needs, and whether Clarivia is the right diligence partner.
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Frequently asked questions (FAQs)
How is this different from traditional technical diligence?
Traditional technical diligence often stays inside architecture and code quality. Clarivia connects technology and product to the GTM engine and the operating model, because that is where thesis risk and value creation usually live.
How do you evaluate AI claims quickly?
We test whether the AI capability is backed by data readiness, governance, and measurable impact. If it cannot credibly move retention, pricing power, or efficiency, it is treated as messaging risk, not a value driver.
Do you produce a first-100-days plan?
Yes. The deliverable is designed to be executable, with sequencing, ownership, and an operating cadence that supports accountability.