Principal-led · White-label delivery
Senior infrastructure judgment for software deals where cost, scale, resilience and operational concentration can change the investment case.
A white-label specialist workstream for Tech DD firms and transaction advisory teams, delivered in 7–10 business days by the principal who performs the analysis and defends the findings.
7–10 business daysRead-only evidenceReport-ready findings
Operator experience
Nikita Tsepov has spent seven years building, operating and improving high-volume, multi-region production systems for revenue-critical software, including a US SaaS unicorn processing billions of dollars in annual transaction volume. His work spans reliability, capacity, security, infrastructure economics, bare-metal operations, deployment systems and high-risk production migrations.
Built and operated multi-region production infrastructure for a US SaaS unicorn processing billions of dollars in annual transaction volume. Availability, capacity and security failures carried immediate customer, revenue and reputational consequences.
Maintained 99.99%+ production availability and completed a five-major-version migration of a critical self-hosted production system with zero downtime and zero data loss. Reduced alert noise by roughly 70%, improving signal quality during real incidents.
Operated and optimized predominantly bare-metal infrastructure estimated to avoid approximately $1.8 million in annualized hyperscaler spend. The estimate reflects a like-for-like AWS/GCP footprint costing approximately $150,000 more per month. Availability, security and operational control were maintained.
Transaction questions
We turn infrastructure evidence into commercially useful conclusions: what is material, what is merely untidy, and what could change the operating model after close.
Does the current infrastructure cost base make economic sense for the product and revenue profile?
What breaks first if transaction assumptions on customers, traffic or data volume are met?
Which operational dependencies create real continuity or key-person risk?
Are resilience, recovery and security controls evidenced, or only described?
Which findings belong in the deal narrative, the 100-day plan or neither?
Assessment scope
The review follows the dependency chain from spend and architecture through failure modes, operating controls and post-close exposure.
Run-rate, spend drivers, commitments, allocation limits and cost sensitivity to growth.
Workload shape, scaling constraints, shared failure domains and capacity assumptions.
Availability design, backup integrity, recovery objectives and evidence from real incidents.
Deployment controls, rollback paths, environment parity and release concentration.
Detection coverage, ownership, escalation, runbooks and dependence on tacit knowledge.
Identity, secrets, perimeter, patching and infrastructure control-plane hygiene.
Material risks, remediation sequence, integration constraints and likely investment needs — drawn together from the six assessment lenses.
From evidence to decision
Each finding connects an observed fact to its commercial consequence and a proportionate response.
01 Evidence
Database expansion requires a maintenance window. No load test validates management’s 3× volume assumption.
02 Finding
The deal case goes beyond validated capacity evidence and depends on a manual scale path with service interruption risk.
03 Transaction impact
Modeled growth may require capacity investment and planned downtime. Cost and timing remain unquantified.
04 Remediation
Review existing performance evidence and capacity modeling; use a targeted load test if feasible within the deal. Cost the options and agree an owner, change window and delivery sequence.
Confidence: Moderate. Current peak utilization is evidenced; 3× capacity and remediation cost remain unvalidated.
100-day priorities
Validate the 3× volume assumption before close through existing performance evidence, capacity modeling or a targeted load test.
Approve the costed capacity plan.
Implement and validate the scale path.
Synthetic example · No client data.
Explore the deliverableMethod
The workstream is scoped against the transaction thesis, uses the existing data room and management cadence, and returns concise findings in the lead team’s preferred structure.
You retain the client relationship and the wider diligence mandate. The work adds focused infrastructure depth, calibrated to the lead team’s materiality threshold.
See the complete workflowEngagement design
Read-only evidence review, targeted management questions and a defined decision boundary keep the workstream fast and proportionate.
Delivery model
Findings are ranked by materiality and written so the lead advisor can integrate them directly into the wider deal narrative.
Conflict profile
The assessment is independent of cloud resale, migration delivery and managed-services revenue.
Direct accountability
Founder & Principal Consultant
Nikita Tsepov is a senior infrastructure operator with seven years of experience across high-volume SaaS, multi-region production systems and security-sensitive infrastructure. He has operated systems processing billions of dollars in annual transaction volume, maintained 99.99%+ production availability and operated and optimized predominantly bare-metal infrastructure estimated to avoid approximately $1.8 million in annualized hyperscaler spend.
That operator background now informs every diligence engagement: identifying which infrastructure findings are financially material, which risks can affect the investment case and what remediation will realistically require after close.
Live transaction
Send the deal context, expected timeline and the current technical diligence scope.