Alexander Lipanov
Founder & CTO, SOFYCOD | AI & Computer Vision Architect | PhD, Applied Mathematics | Patent Holder
35+ years across the full stack of software creation: from low-level code and computer vision research to 25+ years building and leading international engineering teams.
Professional Summary
Throughout my career as a Software Architect, CTO, and Entrepreneur, I’ve navigated the full spectrum of software creation: from writing low-level code and designing enterprise architectures to building and managing cross-functional teams and building Computer Vision and AI-driven solutions.
For 25+ of those years, I’ve been building and leading highly professional engineering teams. Beyond writing code myself, I hire, mentor and structure organizations that deliver software solutions to clients across the EU and USA. Now, I am building an AI-native company.
My research background goes back to 1996, with strong focus on computer vision, predictive modeling and computer vision-based management systems. That foundation drives an AI-native engineering practice at SOFYCOD, where I focus on absolute delivery transparency, detailed requirement validation, and using AI to eliminate engineering friction rather than hide it.
Currently building a unified platform for requirement drafting, delivery planning, and cost estimation alongside a new delivery methodology tailored for an era where AI accelerates code generation, but hasn’t replaced what actually creates value: domain expertise, independent review, and verified result.
Capabilities
Pillars, built over 35 years spanning software development, scientific research, mathematics, computer vision, IT outsourcing, and AI-native software delivery.
Engineering Leadership
Building and leading high-performing engineering teams for 25+ years, focused on effective delivery on time and on budget. Mentoring engineering talent while structuring organizations to consistently deliver custom software of the highest quality.
AI-Native Engineering
Delivery & Methodology
Engineering Company Strategies
Architecture & Domain Depth
My Current Focus
SOFYCOD
Growing an AI-native custom software company with delivery supported by AI tools connected in a single pipeline: from requirements drafting to verified, delivered solutions.
Visit sofycod.com ↗Software Delivery Platform
A unified platform for requirements, user stories, delivery planning, test case generation, cost estimation, code validation, and infrastructure planning, wcreating a single collaborative environment for product owners, managers and engineers.
Delivery Units
A new delivery methodology for the AI Era: pricing by verified units of completed work instead of billable hours. Built on clear definitions of delivery bricks and units created by AI and verified by human experts.
Graph Based Code Review*
A code review approach and methodology combining AI with mathematical models to provide reviewers with automated summaries, visualized architecture maps, and improvement suggestions.
*NOTE: Working title of the methodology I am currently developing.
AI ROI Calculator
A deterministic algorithm combined with LLM tool for honest, conservative ROI estimates across different domains.
Try the calculator ↗Vision-Guided Robotics & Drone Control
Control algorithms for robots and drones driven entirely by camera input. Enables interactive operation through gestures and voice, as well as autonomous execution based on LLM-generated scenarios validated by humans within a visual mission-modeling environment.
My Latest Writings
Insights on AI, computer vision, software engineering, and research grounded on 35+ years of engineering experience and 25+ years of entrepreneurship.
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Hidden Costs That Usually Fall Out of ROI Calculations for AI Implementation
How is ROI for an AI or IT system implementation typically calculated? It usually starts with…
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Classification and Object Detection: From Classical Methods to Current Architectures
The previous article established the distinction between classification and detection in terms of output scale: a…
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Computer Vision Fundamental Tasks
In the previous article we looked at how a computer vision system is built internally is…

