M&A due-diligence and high-load architecture CTO

Source-code due diligence across dozens of apps before acquisition

An acquisition holding was buying consumer apps and needed to know what it was really getting. One of our experts, as CTO for M&A code review, read the source of dozens of apps across Swift, Java, C#, Python, Kotlin and React Native, sized the tech debt, and handed the list to sellers. Hundreds of engineer-days of tech debt were found and pushed to the seller side to fix before acquisition.

Acceptance requirements that sped up onboarding of acquired apps

After each purchase, the internal R&D team had to take over an app built by someone else, and acceptance dragged. One of our experts wrote clear system requirements that acquired apps had to meet for the internal team. The acceptance pipeline with sellers ran roughly twice as fast.

Target architecture that replaced an outsourced analytics team

The holding paid an outsourcing team to run its analytics tooling. One of our experts designed a target architecture for the analytics platform that the company could run without that team, removing a large recurring outsourcing cost (by their own estimate, a seven-figure yearly saving).

High-load endpoints: from tens of thousands to hundreds of thousands RPS per node

Interactive-video services had to serve heavy traffic without an ever-growing fleet. One of our experts, as CTO, led optimization of the backend's high-load endpoints. Throughput per node went from tens of thousands to hundreds of thousands of requests per second, more than an order of magnitude.

Two cloud migrations with infrastructure as code

The company had to move from a local cloud to a public cloud and later into its parent bank's private cloud. One of our experts led both migrations with Terraform and Ansible, so environments became reproducible code. Standing up an infrastructure environment became more than ten times faster.

Getting through investor due diligence from the company side

The company went through several technical due-diligence audits by major investors, including a large bank and a large internet group. One of our experts prepared the engineering side: architecture, CI/CD, monitoring with Grafana and Prometheus, incident SLAs and data-protection compliance. They now know both sides of a due-diligence table.

Leading a multi-platform team across around a hundred repositories

The company ran dozens of backend services, DevOps repos and mobile apps, with video transcoding and HLS/DASH delivery. One of our experts led a team of a few dozen engineers across backend, frontend, iOS, Android and DevOps, grew them through training, and kept a high-six-figure engineering budget on track.

Consumer app from scratch to over a hundred thousand users

A startup needed its product built from zero. One of our experts, as CTO, built the iOS app (Swift) and Java backend, moved infrastructure from on-premise to the cloud with infrastructure as code, and grew the user base past a hundred thousand. They also made the case to the mobile app stores that the items sold were not digital goods, which kept the platform commission off that revenue.

Low-latency trading bridge for banks

Banks needed a bridge between a retail trading platform and their FIX-based liquidity infrastructure. One of our experts built and released a C++ bridge handling tens of thousands of requests per second for banks in several countries; clients' transaction volume roughly doubled.

Public-sector portals for hundreds of thousands of people

One of our experts designed and built a utility customer portal for individual accounts (a couple of hundred thousand people) and thousands of business accounts, and a portal for a medical university's doctors and students (tens of thousands of users).

LLM-agent tooling that recovers architecture from source code

Documentation goes stale and large codebases outgrow anyone's head. One of our experts, as CTO of a developer-tools startup, built a system that reverse-engineers architecture from Java/Spring Boot source and produces architecture docs and diagrams (C4, data-flow, sequence). It uses multi-agent LLM pipelines, RAG, an MCP server, and chunking plus graph indexing for codebases larger than a context window. It ran in pilots with large enterprises.

Architecture recovery for an AI-generated codebase

A founder built fast with AI coding tools and no longer knows how the pieces connect: services call the database directly, layers are bypassed, and every change breaks something.

Map the actual architecture from the code (components, data stores, queues, dependencies), mark where layer boundaries are broken, and agree on rules the team and its coding agents should follow.

Kafka and microservice-pattern review for a growing backend

A team split a monolith into services and now has a "distributed monolith": synchronous call chains, unclear ownership of transactions, and messages that get lost.

Review messaging (sync vs async over Kafka), long-running transactions (Saga), read/write separation (CQRS), Backend-for-Frontend layers and the repository layout for Java services.