Svitlana Khimka

• 70% — Adoption Rate
• 20% — Retention Rate

The client needed to rapidly introduce AI capabilities into their product to respond to shifting user behavior and increasing competitive pressure. They lacked a clear AI strategy and required a production-ready solution that would deliver measurable business value, not just experimentation.

• Facilitated a strategy and competitive analysis workshop to identify high-impact AI opportunities aligned with product and market positioning.
• Defined a clear AI roadmap focused on value creation and user adoption.
• Led the integration of GenAI into the product, including a customer-facing data finder agent that uses agentic decision flows to collect and enrich data while optimizing for cost and accuracy.
• Ensured scalability, reliability, and seamless integration into the existing product ecosystem.

• Achieved 70% feature adoption among active users.
• Improved month-over-month retention by 20% for users who adopted the AI features.

Latana is a SaaS B2B product entering the growth stage. My task was to evaluate the current state of the product and market conditions to propose a 2-year product strategy and roadmap of key initiatives.

To accomplish the project, I led the following activities:
• worked closely with the founder of the company to define key points of product vision and strategy;
• competitors and market landscape analysis;
• SWAT analysis of the current product;
• performance assessment of the current product features;
• customer research to better understand their needs; and
• brainstormed the features ideas with the team.

Latana is a brand analytics solution producing data for clients. The company runs a complex set of business processes, including project management, data collection, data cleaning, and modification with machine learning algorithms.

I introduced automation to allow the company to increase the number of projects without scaling the team. To achieve the objective, I managed the following:
• introduced the system of operational metrics for a better overview of bottlenecks and current capacity;
• mapped out business processes and dependencies between them;
• analyzed the main bottlenecks and challenges based on the data from the activities mentioned above;
• developed a prioritized roadmap of product initiatives to address the key issues; and
• managed the roadmap execution.

Yuno Surveys is a research community where users can participate in market research studies and get rewarded.

My task was to launch the product from scratch and lead it through the initial growth. During this project, I managed the following activities:
• developed the initial product concept;
• created a go-to-market strategy;
• built an MVP;
• developed the 6-months product roadmap and managed its execution;
• managed paid marketing activities; and
• built a team to manage the project, including the product, tech, customer success, and marketing team.

Latana is a SaaS B2B product. My task was to develop the next version of the product based on the company strategy and business objectives.

To accomplish the project, I led the following activities:
• assessed the current state of the product;
• ran ideation session and customer discovery call to define the backlog of potential features;
• developed a go-to-market strategy and managed MVP development and launch;
• defined a roadmap of high-impact features, release and tests plans for them; and
• oversaw roadmap execution and feature launches.

As part of this project, I performed the following tasks:

• Collaborated with key stakeholders to gather requirements and insights.
• Defined the product strategy and created a high-level roadmap.
• Developed an initial go-to-market and pricing strategy.
• Worked with the tech and design teams to prioritize features and define the scope of the MVP version.
• Prepared feature requirements and specifications.
• Coordinated the MVP launch plan with the marketing and customer support teams.

• 40% — GMV

The client needed to deliver critical platform features rapidly, but was dissatisfied with the development speed and execution. Product processes were unclear, the scope was not well defined, and delivery lacked alignment across stakeholders.

• Established structured product processes, including clear prioritization, roadmap planning, and stakeholder communication.
• Defined and scoped the missing platform features with measurable delivery milestones.
• Worked closely with engineering to accelerate execution and remove delivery bottlenecks.
• Led the build of a U.S.-focused automotive marketplace connecting dealers and lenders.
• Implemented AI-powered credit scoring, lender and dealer integrations, and compliance workflows to support scalable marketplace operations.

• Accelerated product delivery by implementing structured product processes and clearly defining feature scope.
• Drove a 40% increase in gross merchandise value (GMV) through improved platform efficiency and faster transaction workflows.

The client wanted to ensure their product and engineering teams were leveraging modern AI tools to remain competitive. They also aimed to embed AI into internal workflows to increase productivity and reduce operational costs.

• Led AI adoption initiatives across product and development teams, integrating modern AI tools into daily workflows.
• Coached teams on practical applications of generative AI to improve delivery speed and quality.
• Facilitated strategy sessions to identify high-impact AI use cases for streamlining internal operations.
• Defined a structured AI implementation roadmap aligned with business priorities.

• Established a clear AI roadmap with prioritized initiatives.
• Improved team productivity through workflow automation and AI-assisted development practices.
• Identified cost-reduction opportunities through AI-enabled process optimization.

The client wanted to launch a generative AI tool for writing high-quality email newsletters. They needed a product lead who could quickly validate the concept, define the MVP scope, and work closely with engineering to bring a production-ready feature to market under tight timelines.

• Led rapid discovery to define target users and MVP scope.
• Designed core workflows from prompt to export-ready newsletter.
• Translated requirements into clear user stories and acceptance criteria.
• Partnered closely with engineering to ship a production-ready feature within tight timelines.

• Delivered a customer-ready MVP within one month
• Established a scalable foundation for future AI-driven enhancements.

• 50 — Customer Growth in 12 Months
• 80% — AI Assistant Adoption

• The company needed to define an AI-native booking reservation workflow from scratch.
• Founders had strong restaurant domain expertise but limited experience with technical trade-offs.
• Team needed a clear MVP roadmap that prioritized speed over complexity.
• Product had to be ready quickly so the company could start onboarding early customers.

• Led product discovery with founders and early customers.
• Translated restaurant workflows into AI product requirements and delivery priorities.
• Defined the MVP roadmap for an AI booking assistant, including intake, data extraction, availability checks, and suggested replies.
• Prioritized fast delivery and reduced scope creep, helping the team move from concept to customer onboarding.

• Built the product foundation that supported growth toward 50 customers within 12 months.
• Built in native AI capabilities with 80% adoption rate.