Even the strongest AI initiative can fail during implementation. The reasons often lie in technical issues, incomplete data, overlooked team limitations, or internal resistance to change. That’s why it’s not enough to build a strategy — it must be translated into action, with close attention to detail, risks, and the nuances of the operational environment.
Implementation support is hands-on work: launching AI scenarios in real-world conditions, validating assumptions, managing risks, and continuously adapting as the project evolves. I act as an external AI product lead or strategist — not replacing the team, but helping them move from idea to working tools embedded in daily operations.
What’s included in the service:
- Support in developing technical requirements and product specifications
- Validation of solution architecture and implementation logic
- Guidance on selecting vendors, platforms, and contractors
- Setting up pilot processes and hypothesis testing workflows
- Facilitation between business and technical teams
- Adapting the implementation strategy based on feedback and iterations
- Monitoring achievement of target outcomes (cost, time, quality)
- Strategic input on scaling decisions and next steps
What you get as a result:
- A managed and structured launch of AI initiatives into your business environment
- Risk mitigation across technical, operational, and resource areas
- Time and budget savings by focusing on MVP and lean iterations
- Team involvement without overload — thanks to clear communication and integration tactics
- Confidence that your AI solution will go beyond a pitch deck — and work in production
This approach is particularly valuable when your business requires operational control, measurable results, and minimal disruption to internal workflows.
Selected Case Studies
1. Messaging platform with chatbot constructor
As a lead product manager, I initiated and delivered a project to replace custom chatbot development with a scalable solution. After auditing the current workflows, I prepared the technical specification, designed the implementation strategy, and developed the rollout plan. I selected and customized a suitable chatbot builder tailored to platform needs. The result: development workload was reduced by over 70%, and the launch speed of new bots significantly increased.
2. HR platform for industrial staffing
A self-launched startup project — taken from idea through MVP to monetization. I led all key stages: hypothesis testing, product development, and go-to-market. A core challenge was minimizing worker drop-offs after accepting assignments. The solution involved implementing matching logic based on behavioral data, plus product mechanisms to improve worker reliability and motivation. This led to reduced operational costs and a higher completion rate.
3. Online education platform
In the role of product manager and implementer, I led the development of an AI-based customer support assistant. I was responsible for the entire cycle: defining the problem, selecting tools, designing dialogue flows, and launching the solution. The goals: reduce support load, increase response speed, and improve satisfaction. The assistant helped reallocate team resources and improve service consistency.
Over the course of my product career, I’ve delivered 100+ projects — from internal tools to client-facing systems, from MVPs to large-scale implementations. This hands-on experience allows me not just to launch AI-powered solutions, but to build sustainable product frameworks — from idea to execution and performance tracking.
Why Clients Choose Me
I combine strategic thinking, startup experience, and deep expertise in generative AI. I speak the same language as founders and product leaders — while also understanding what’s happening under the hood of AI models and tools.
I work fast, focus on substance, and avoid fluff. My goal is not just to “add an AI feature,” but to identify the exact point where AI creates real business value — cutting costs, speeding up processes, or improving decision quality.
In every project, I bring a combination of:
- 12+ years of experience in IT and product development;
- 3 years of hands-on work with LLMs and AI automation;
- Dozens of AI consultations and implemented solutions across industries.
My approach is built on clear diagnostics, pragmatic recommendations, and actionable plans that account for your goals, constraints, and resources.