cases

Channels: Google Ads, Meta Ads
Monthly Budget: €400
Monthly Requests: 30
What We Did: Segmented services based on keywords and advertising offer, and targeted selected countries.
Result: Attracted new clients for training, increased school awareness, and increased engagement in Meta Ads.

Channels: Meta Ads, Google Ads, Bing Ads, Criteo
Monthly Budget: $140,000
Monthly Sales: 3,300
What We Did: We developed effective targeting and personalized the service for the user.
We used bidding strategies and keywords to appear higher in search results than competitors.
Result: We increased conversion by 1.5 times and successfully launched new advertising services.

Channels: Meta Ads, Google Ads
Monthly Budget: $10,000
Monthly Sales: Average 250
What We Did: Rebuilt the funnel in Meta Ads, set up remarketing correctly, optimized the product feed in Google Ads, and set up PMax.
Result: CPS was reduced by almost half while scaling the budget.

What we did: We created a funnel for users from scratch, highlighting the app's benefits and a trial version.
Result: With a low app install cost, we achieved a high conversion rate to subscription payments.
Channels: Meta Ads, Google Ads
Monthly budget: €2,000
What we did: We created a funnel for users from scratch, highlighting the app's benefits and a trial version.
Result: With a low app install cost, we achieved a high conversion rate to subscription payments.

Channels: Google Ads
Monthly Budget: $1,000
Requests per Month: 60
What we did: Launched a landing page for legalization services, set up a target group and keywords for the ideal client.
Result: Over 50 requests per month. Average price per request: $17, with the service price being $600.

Focus: AI Automation
Format: Web application, integration with medical systems
Problem: doctors spent 10–15 minutes after each appointment filling out medical documents.
What we did: built an AI solution that automatically transcribes doctor–patient conversations and fills in medical documents in real time, adapted to medical terminology and data privacy requirements. Result: documentation time reduced from 15 minutes to 15 seconds, lower workload for doctors, and standardized, higher-quality medical records.

Focus: AI Development
Platform: Telegram
Timeline: 3 weeks
Problem: the client needed an educational bot for school students and university learners, with an easy interface, support for different formats, and built-in monetization.
What we did: developed an AI educational bot that handles text and voice messages, solves study tasks, explains topics, and works with files. Added an admin panel, payments, a free trial, and a referral program.
Result: a fully functional educational Telegram bot with monetization and scalability built in.

Focus: AI Development
Platform: Telegram
Timeline: 6 weeks
Problem: the client needed to automate cosmetic product analysis and personalized recommendations, with monetization from day one.
What we did: built an AI bot that identifies skin type, analyzes products by photo or name, and suggests alternatives. Implemented subscriptions with auto-renewal, payments, referral system, and promo codes. Result: launched an AI bot with a working monetization model and automated, personalized cosmetic analysis.

Focus: Business Process Automation
Platform: Telegram
Timeline: 1 week
Problem: the existing lead distribution system did not separate new and old leads, reducing sales team efficiency.
What we did: optimized the Telegram bot by splitting lead flows (new leads vs. leads from the database), adding separate limits, keeping existing KPIs, and updating the system without downtime.
Result: higher manager productivity, clear lead distribution, and a flexible system ready for further AI optimization.

Focus: AI Automation for 1C
Status: Ongoing project
Problem: manual formatting of product names for 1C took a lot of time, caused errors, and increased staffing costs.
What we did: developed an AI system that automatically recognizes product parameters, converts names into the required 1C format, and integrates without changing existing workflows.
Result: input errors eliminated, order processing accelerated, and staff reduced by 5 people through full automation.