Operator-Led Technical Diligence

Technical diligence for private equity, from underwriting through execution.

I represent private equity in software transactions where the technical condition of the business can affect price, structure, or the operating case.

Every diligence client to date has elected to retain me post-close, including those I advised required no remediation.

Next availability · April 2027

05
transactions as exclusive technical advisor
08
portfolio companies with additional value creation work
100%
of diligence clients retained post-close
The deal teams that call me have commissioned enough CrossLake and West Monroe reports to know the difference between diligence performed as ceremony and diligence performed for an investment decision.

Blackmere is principal-only. The person who examines the systems presents the findings and, when retained, carries them into execution.

Mandates

Selected Outcomes

Representative work across diligence, post-close execution, and portfolio-level advisory. Some of it changed the facts used to understand a business. Some changed the economics or the systems themselves.

Economics and Operating Truth

Re-derived a target’s paying-customer count and cohort net revenue retention directly from its production database, then reconciled both against management’s own queries
Reduced CloudFront costs by 60% and compute costs by 40%, directly expanding EBITDA
Built two reconciliation engines covering both directions of a portfolio company’s money flow, from card charges into the platform through payouts to its merchants, reconciling more than $20 million of monthly transaction volume against the payment processor’s own records ahead of the annual audit
Identified and resolved a recursive request loop outside the scope of a post-close engagement, cutting web traffic by 50% and eliminating the corresponding downstream costs in observability and logging
Built an engineering health baseline across ten companies in a middle-market private equity portfolio, measuring delivery discipline, QA, observability, and change-failure rate on common standards

AI and Modernization

Built an AI-native document ingestion engine that reduced a 45-day manual process to one business day, automating classification and extraction across more than 100,000 legacy documents per invocation
Implemented batch AI processing that reduced the cost of the workload by roughly 50%
Deployed role-specific AI agents across sales and account management, engineering, DevOps, QA, support, IT, design, production alerting, and executive stakeholders, connected to the company’s CRM, data warehouse, production database, and observability stack

Security and Infrastructure

Deployed enterprise-grade web application firewalls across portfolio companies, closing security gaps that had persisted since inception within weeks
Built modern Firebase authentication for a Flutter-based mobile application serving millions of users
Delivered cloud-native, self-service SSL white-labeling capability inside a legacy codebase
Completed a network re-architecture and production deployment after years of internal stagnation
Migrated production to us-east-1 with zero downtime
Implemented business continuity planning and cross-account, multi-region disaster recovery

The Model

Principal-Only

No analyst layer. No subcontractors. No delivery pyramid between the person who found the fact and the person explaining why it matters.

Diligence Through Execution

The remediation plan is written by somebody who may have to execute every sentence in it. That tends to improve the quality of the prose.

Capacity-Constrained

A limited number of concurrent mandates. A firm expected to enter a portfolio company after close needs room on the calendar.

There are limits to what diligence can establish before close. Blackmere quantifies what it can and states what remains unknown. A complete remediation program cannot be scoped from a data room when production access or operating authority is required to know what the work entails.

The Principal

Blackmere is the practice of Mo Battah.

Before founding it, he was the principal executive responsible for Alpine Investors’ largest software roll-up, Actabl, integrating four companies into a unified platform. Before private equity, he scaled engineering through VC-backed hypergrowth from Series A through a $1B+ valuation. He has run full-stack engineering, cloud infrastructure across AWS, Azure, and GCP, SRE, DevOps, and cybersecurity across multi-product portfolios.

The practice itself was created by private equity demand. A fund approached him during his transition out of Alpine. That first mandate became buy-side diligence and then post-close execution. Another transaction required sell-side representation. The service lines followed the work.

He also invests directly. A SAFE in Kodiak Robotics returned 4.8x MOIC in under a year. As an LP in Aviso Ventures, his portfolio includes exits to Palo Alto Networks, Dropbox, and SpaceX.

That puts him in deal rooms in two capacities: as the person examining the technology and as an investor committing his own capital. The distinction is useful because technical diligence eventually reduces to a capital-allocation question: which technical facts deserve money, time, or attention, and which do not.

Selected Writing

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Direct Access

For 2027 mandates, send a brief overview of the asset and expected transaction timing to mo@blackmere.ai.