Our Work

What we've seen in the field.

Our experience spans dozens of transactions across software, infrastructure, and emerging technology companies, from pre-LOI diligence to post-close integration execution.

Confidentiality

Deal specifics stay confidential.
The outcomes don't.

By nature of the work, we're often operating under strict NDAs. We don't disclose client names, target companies, or deal terms without explicit permission.

For qualified buyers, we share anonymized findings, outcome data, and sample deliverables that illustrate the depth and format of our work. Reach out to request them.

Request Sample Materials

What our work has produced

Renegotiated deal terms after findings

Material architectural debt identified in diligence gave buyers leverage to renegotiate price and representations before signing.

$2M+ in avoided post-close infrastructure costs

Scaling limitations flagged pre-close, completely absent from seller materials, allowed the acquirer to price in the remediation cost.

Deal walk-away on a $120M acquisition

Findings report surfaced that the platform couldn't support its core product roadmap. The buyer walked. The deal was a bullet dodged.

Integration timeline cut from 18 months to 7

Integration architecture sequenced around actual system dependencies rather than assumptions compressed time-to-value dramatically.

Transaction Experience

Across industries, deal stages, and system types.

We've seen the full range, from clean, well-documented platforms to undocumented legacy systems with years of accumulated debt.

💳
Fintech & Payments

High compliance, high complexity

PCI/DSS scope, payments infrastructure, fraud systems, regulatory compliance gaps, and core banking integrations.

☁️
SaaS Platforms

Scalability and multi-tenancy

Architecture for scale, data isolation, API design, onboarding automation, and whether the platform can support the next 10x in customers.

🔄
Marketplaces & Networks

Two-sided complexity

Supply/demand matching systems, trust and safety infrastructure, identity management, and the technical moats that protect network effects.

🏭
Enterprise & IoT

Legacy modernization risk

On-prem to cloud migrations, embedded system dependencies, custom hardware integrations, and multi-decade technical debt.

🤖
AI & Data Platforms

Pipeline viability and data moats

ML model maturity, training data quality, inference infrastructure costs, and whether AI claims in the pitch deck hold up under scrutiny.

🔧
Developer Tools & Infrastructure

Open source exposure and lock-in

Licensing risk, open source dependencies, build system debt, and the engineering org dynamics that make or break developer-focused acquisitions.

Sample Materials

See what our diligence reports look like.

We share anonymized findings and sample deliverables with qualified buyers on request. No commitment required.

Request a Sample Report

All materials shared under mutual NDA.