Personal AI assistant
Write or send a voice note in Telegram — the assistant creates tasks, searches your data, drafts emails, calculates and reminds. All the small routine passes you by.
Complex systems, turnkey — from architecture to production
We take on any type of project, from an internal accounting system to AI automation. They have one thing in common: each has to be designed, not assembled from a template.
- 10
- years in business
- 50+
- projects
- 30+
- clients
- 11
- different industries
Our systems1 / 8
Services
What we can build
Five areas we work in most. Each covers both tasks that take a few weeks and systems that take months.
CRM and internal systems
Orders, stock, production, payroll — in one system instead of seven spreadsheets and a chat.
- ✓We map your current process first and tell you which parts are not worth automating
- ✓Roles and permissions are designed around real job titles, not “admin / not admin”
- ✓Legacy data import is a separate stage: we show you what is dirty in it before we start
AI automation
Enquiry handling, data extraction from documents, search across your internal knowledge, classification and routing.
- ✓A pilot on your own data first — before you pay for development
- ✓We measure accuracy and give you the number: 92–97% on enquiry classification in practice
- ✓Whatever the model cannot handle goes to a human with full context, not “sorry, I did not understand”
Integrations
Accounting, website, marketplaces, telephony and bank start exchanging data without a human in between.
- ✓Queues and retries: if someone else’s service goes down, data waits instead of disappearing
- ✓An exchange log your own admin can open and read without us
- ✓We tell you upfront where a system has no API and what that means when it gets updated
Web services and portals
Client portals, platforms, marketplaces — from architecture to production and support.
- ✓Load is designed into the architecture from the start, not rewritten a year later
- ✓We build mobile-first: desktop is added on top, not the other way around
- ✓Pages are served as ready HTML — they open fast and index properly
Mobile apps
Android and iOS — from an app for field staff to a client portal in your customer’s pocket.
- ✓Built as part of the system, not separately: app and backend are designed together
- ✓Works offline and syncs the data once the connection is back
- ✓We tell you upfront when a mobile website is enough and an app is not needed
Your task is not on the list?
Mobile client portals, parsers, bots, legacy migrations, taking over someone else’s system, non-standard integrations — we do those too. Describe the task and we will honestly say whether we take it, and why.
Work
Systems we have built
We take on any task — the type of project is not a limit. Every system below went through the full cycle with us: architecture, development, launch into production and support afterwards. Below is part of what we have built.
Utilities
Waste collection automation
Every morning drivers received a printed list of collection points, and dispatchers learned about problems only in the evening, when trucks came back. We built a tablet app with routing and photo confirmation at every point, a live dashboard with trucks on a map, separate apps for customers and landfill operators, and a two-way integration with 1C. Mileage and fuel are calculated from GPS automatically.
Result
No paper left in the process: dispatchers see trucks on a map, every point is confirmed with a photo
JavaSpring BootAndroidPostgreSQLWebSocket1C
Manufacturing
Made-to-order manufacturing automation
Orders arrived through Instagram, a manager printed them and carried a stack of paper to the shop floor at the end of the day. The only way to learn an order status was to walk there. We connected the CRM to production: an order reaches the floor the same minute, workers see tasks on screens, stages switch automatically.
Result
2–3 days→4–16 hours
JavaSpring BootAngularPostgreSQLRabbitMQ
Sales
CRM and ManyChat integration
ManyChat conversations lived separately from the CRM: a manager created deals by hand and then searched for who exactly they had talked to. We built a server-side integration with two-way sync and a browser extension with buttons that jump from a chat to a deal and back.
Result
No lead from a conversation gets lost or entered by hand anymore
Node.jsREST APIWebhooksChrome Extension
Internal systemsopen ↗
RevukCRM — our own CRM
Off-the-shelf CRMs did not fit our own processes: half the fields were useless, the ones we needed were missing, and bending someone else’s product cost more than writing our own. So we built one — deals, clients, tasks, roles and permissions mapped to real positions — and we run our work in it every day.
Result
We run all our own projects in it — and see first-hand how it behaves under load
JavaSpring BootAngularPostgreSQL
AI automationopen ↗
Personal AI assistant
Small routine ate half of the working day: remind about a call, find a document, do the maths, create a task. We built our own assistant in Telegram — you write to it or send a voice note, and it creates tasks, searches your data, drafts emails, calculates and reminds. We use it ourselves every day.
Result
Small routine no longer takes the owner’s time
PythonClaude APITelegram Bot APISpeech-to-TextPostgreSQL
AI automation
AI worker inside the CRM
Chats came through Instagram, Telegram and the website at the same time, and in the evenings and on weekends nobody answered them. We built an AI worker that replies around the clock, qualifies enquiries and collects contacts — and in parallel creates the deal in the CRM and moves it through statuses.
Result
Customers get an answer at any hour, and the CRM fills itself without a manager
PythonClaude APICRM APIWebhooksPostgreSQL
Internal systems
Corporate messenger
Work conversations lived in employees’ personal Telegram accounts, and when someone left, the whole negotiation history left with them. We built an internal messenger on the company’s own server: channels, files, searchable history and access rights.
Result
Negotiation history stays with the company after an employee leaves
JavaSpring BootWebSocketAngularPostgreSQL
Sales
Call assistant for sales reps
During a call a manager searched for the product in a price list, then for stock in the accounting system, and recalled what to say on the fly while the customer waited on the line. We built an assistant that shows the product card, stock, price and a conversation script for the exact situation the moment a call comes in.
Result
A newcomer answers a customer as confidently as an experienced manager
AngularNode.jsREST APITelephony
Education
Hosting for student websites
Students were learning to build websites but had nowhere to publish them, and giving each of them a separate server meant an unmanageable zoo. We built a platform where a student publishes a site in two clicks and a teacher sees the whole class’s work in one place.
Result
Students publish their work themselves, the teacher spends no time on setup
DockerLinuxNginxNode.js
Education
NFC attendance register
Attendance was marked by hand at the start of a lesson, then transferred into a register, the numbers diverged, and parents learned about absences late. We built NFC-based tracking: a student taps a chip at the entrance, and the register and reports build themselves.
Result
The register fills itself and attendance numbers finally match
JavaSpring BootAndroidNFCPostgreSQL
Integrations
CRM integrations
A manager copied the address from a conversation into the delivery service, and the tracking number back into the CRM — half a working day and half of all errors came from that. We connected Nova Poshta, Ukrposhta, Instagram, Telegram and Facebook to the CRM: enquiries from every channel arrive on their own and a waybill is created straight from the deal.
Result
Enquiries and waybills flow through without a single manual copy-paste
Node.jsREST APIWebhooks
E-commerce
Product reservation across a retail network
A buyer called several shops to find out whether an item was in stock, and the shop held it “verbally” and then lost the reservation. We built a service where shops publish real stock levels and a buyer sees them online and reserves an item at a specific location.
Result
Buyers see real stock online and shops stop losing reservations
JavaSpring BootAngularPostgreSQL
Finance
Income and expense tracking
Monthly earnings were counted in a spreadsheet and came out different every time, while where the money had gone was reconstructed after the fact. We built income and expense tracking by category: balances across cash desks and accounts are visible at any moment, and reports are generated for any period.
Result
Income, spending and balance are visible at any moment, not at month end
JavaSpring BootAngularPostgreSQL
Analytics
Analytics on top of Google Sheets
The data already lived in Google Sheets, but seeing the whole picture meant merging it by hand every time. We built analytics on top of those very sheets: data is pulled in, consolidated into a dashboard and refreshed without manual work.
Result
The report builds itself — manual merging of spreadsheets is no longer needed
Node.jsGoogle Sheets APIAngular
Analytics
End-to-end studio analytics
Revenue was visible but profit was not: nobody counted how many hours went into a particular client and how much that client actually brought in. We built end-to-end analytics from the first chat message all the way to the money — per client.
Result
Profit is visible per client, not just total revenue
Node.jsPostgreSQLAngular
Online productopen ↗
Babusya
The client had a product idea and no team to build it. We delivered the platform turnkey — design, frontend, backend and deployment: conversations with the character, advice, horoscopes, dream interpretation, palm reading from a photo and numerology.
Result
The product went from zero to production without any team on the client’s side
AngularSpring BootPostgreSQLTailwindCSS
Process
How we work
A transparent process from idea to launch.
01
Discovery
3 days
We study your processes and dig into the task: what hurts, what software can actually solve and what it cannot.
02
Spec and architecture
1–2 weeks
System diagram, data model, list of screens, integration points and a stage plan with an estimate for each.
03
Design
1–3 weeks
UX and mockups for every screen, built around your scenarios. Signed off before development starts.
04
Development in stages
2–6 weeks / stage
Every stage ends with a working feature on a staging environment that you can click through.
05
Testing and launch
1–2 weeks
We test scenarios across devices, migrate the data, deploy to production and hand over the access.
06
Support
After launch
Fixes, updates and further development after launch. Scope and response times are agreed separately.
Stack
What we work with
The stack is ordinary and widespread — which is exactly why any mid-level developer can pick your system up, not only us.
Backend
JavaSpring BootJPA/HibernateNode.jsNestJSPythonREST API
Frontend
AngularReactVue.jsNext.jsTypeScriptTailwind CSS
Databases
PostgreSQLMySQLMongoDBRedisElasticsearchpgvector
Queues & real-time
RabbitMQKafkaActiveMQWebSocketSocket.io
Mobile
AndroidKotlinSwiftReact NativeFlutter
Infrastructure
DockerLinuxNginxCloudflareVercelSSH/SSL
AI & automation
ClaudeOpenAIRAGChatbotsAI assistants
Integrations
1CNova PoshtaUkrposhtaInstagramTelegramFacebookGoogle Sheets
FAQ
What people ask on the first call
+How much does building a system cost?
From $500 — that is the floor: a small improvement or a single integration. A full system costs more, and how much more depends on the number of integrations and how dirty your current data is. The exact figure comes out of the spec; before that any number is a guess, ours included.
+How long does a project take?
Discovery takes 3 days. The spec takes 1–2 weeks. Then stages of 2–6 weeks each. A mid-size project runs 3–5 months from the first meeting to a working system. The timeline grows exactly as long as decisions take on your side; we put that in the estimate as a separate line.
+We already have a system built by someone else. Will you take it over?
Only after a paid code audit — 3–5 days. We do not take it on blindly: estimating someone else’s codebase without looking means being wrong by a multiple. After the audit we tell you honestly which is cheaper — extending it or rewriting.
+Does AI actually work, or is it a demo for investors?
It works on narrow, well-defined tasks: enquiry classification, data extraction from documents, standard replies, search across internal knowledge. Accuracy is 92–97% in practice, and where the remainder goes is designed in from the start. An “AI employee that replaces a department” is not something we sell.
+Do you work with clients abroad?
Yes, remotely. Paperwork in English or Ukrainian. A time difference of up to 3 hours is fine; anything larger we discuss separately, because it slows down decision-making.
First step
Tell us what you need
Write two sentences about what is happening and what you want instead. We will look, ask clarifying questions and tell you whether it is a task for us.
- ✓What is happening now and what of it software can actually solve
- ✓Whether it is worth automating at all
- ✓Rough scope of work and what the price will depend on
- ✓Whether we take on a task like this
We name an exact price and timeline only after we understand the task. Before that any number would be a guess — ours included.