When a customer or teammate already works in Telegram: submitting a request, choosing a service, paying, receiving updates or browsing a catalogue.
See a subscription flow →Services
Five areas of expertise. We take the whole task from logic and data to production deployment, and choose the format around the working scenario rather than a fashionable technology label.
Telegram bots & mini apps
Lead capture and sales, payments and subscriptions via Stripe/Telegram/YooKassa, a catalog with a cart, booking, a personal account. From a simple bot to a full mini app that looks native but lives right in the messenger.
{{ priceTelegram }} case study: subscription service →AI assistants & agents
There's a real LLM inside, but it answers strictly from your materials: prices, services, documents, common questions. The assistant qualifies the lead, takes the routine first line of support, and hands a human what actually needs a human. No made-up answers instead of facts.
{{ priceAi }} case study: AI-powered CRM →Integrations & automation
We connect CRM, marketplaces (Ozon, Wildberries, Amazon) and any service via API. We take the manual routine off your hands: parsing, reports, exports, price recalculation, data sync. What a person does by hand every day starts running itself.
{{ priceAutomation }} case study: autopricer for Ozon →Web services & apps
Personal accounts, dashboards, admin panels, internal tools and SaaS built for your task. We take the whole cycle: database, logic, interface, launch on a server. One service can serve many clients with fully isolated data.
{{ priceWeb }} case study: VetPulse, a web CRM →Mobile apps
iOS and Android from a single codebase with Flutter: faster and cheaper than two separate builds. Offline mode, payments, push notifications, publishing to the App Store and Google Play.
{{ priceMobile }} case study: Faith App →What fits your task
We start with where the work happens, how often the scenario repeats and how many roles are involved. A useful first version does not have to begin as a large system.
When data already lives in a CRM, ERP or marketplace, but people still copy it, reconcile spreadsheets or recalculate indicators every day.
See pricing automation →When the process needs separate roles, a shared database, an audit trail, dashboards and a workspace available from any computer without installation.
See a multi-user CRM →When the product must stay close at hand, use system notifications, the camera or offline data, and be distributed through app stores.
See a Flutter application →Common questions
Where do we start without a technical specification?
Describe the working scenario: who does what today, where time or requests get lost, and which services are already in use. We will map the first useful version, its dependencies and the next possible stages.
How do you choose between a bot, a website and an app?
We look at where the action is most convenient, whether roles and a shared database are required, whether offline access matters, and how often the process changes. If a bot or background automation solves it, we do not suggest a more expensive format.
How are the price and scope fixed?
Before work begins, we agree on the first version, acceptance criteria, price and timing. Features outside that agreed scope are estimated separately, without silently expanding the budget.
Can you continue an existing product?
Yes, when the current codebase and access model allow safe development. We first review the repository, architecture and release path; if continuing is risky, we explain the concrete reason and propose a migration route.
What is included in the handover?
We agree on the handover before work starts: the working release, agreed source files, deployment configuration and a verification scenario. Secrets never go into a public repository and are transferred separately through a safe channel.
What happens after launch?
For seven days, we fix defects in the agreed functionality. Further development, monitoring and support depend on the product and are agreed separately.