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Case studies / what we build

Project Examples and the Problems Behind Them

We can't show every project, and client work is often confidential. What we can do is describe the kinds of problems we take on, how we approached them, and what the work involved.

Web platforms Mobile apps AI automation

Reading time

Nine situations we see often

What these have in common

How to read these examples

Each entry below describes a real shape of engagement: the situation the client came with, the constraint that shaped the build, and what the delivered work actually involved. Client names and confidential details are left out. The problems are not.

If one of these resembles your situation, that's a useful starting point for a conversation. If none of them do, that's useful too, because it means we're describing the wrong problems and we'd rather hear yours first.

A retail chain with disconnected branch systems

Web platform

Central catalog and daily reconciliation

A mid-sized retailer ran separate stock and sales records per branch, reconciled by hand at month end. Staff spent days matching numbers that should have agreed automatically.

We built a central web platform with one product catalog, branch-level inventory, and daily reconciliation. The design work focused on the counter workflow, since staff needed to complete a sale in seconds during a rush. Integration with the existing cash registers was the hardest part and got scoped first.

A mobile app for a service business

Mobile app

Booking, reminders, status view

A services company wanted customers to book and track appointments without phone calls.

We built a cross-platform mobile app with booking, reminders, and a simple status view. The interesting constraint was language: the same screens had to hold Kazakh, Russian, and English labels without breaking. We designed with the longest strings from the start. Push reminders cut no-shows, but the bigger win was that staff stopped answering "what time is my appointment" calls.

An AI assistant for routine customer questions

AI solutions

Answers and routing, with escalation rules

A company with a small support team faced the same thirty questions every week.

We built an AI agent that answers the rules-based ones and routes everything else to a person, with the full conversation attached. The agent runs at any hour, which matters because a share of queries arrive outside working hours. We defined escalation rules before building, including what the agent must never answer on its own. The team's workload shifted toward complex cases.

A dim office desk at night with supplier envelopes stacked in soft foreground blur

Document processing for a finance department

Document pipeline

Extraction, matching, review flags

An accounts team was manually entering data from hundreds of supplier invoices a month.

We built a pipeline that reads each document, extracts the key fields, checks them against purchase orders, and flags mismatches for review. Accuracy on clean digital invoices was high from the start; scanned and photographed documents needed more tuning. The design decision that mattered most was showing the reviewer exactly which field came from which part of the document.

An internal tool replacing spreadsheets

A logistics company tracked shipments in a shared spreadsheet that had grown into a liability: no access control, no history, frequent conflicts.

We rebuilt it as a web application with roles, an audit log, and automated status updates from carrier data. The team resisted at first, so we ran both systems in parallel for three weeks and let the spreadsheet lose on its own. Documentation and a short training session covered the handover.

A night logistics depot floor with a worker checking a handheld device under one lamp

A public-facing website with real load requirements

Turnkey website

Editable content, performance budgets

A regional organization needed a site that could handle traffic spikes during announcements and stay usable on slow mobile connections.

We built a turnkey website with a content system the team could edit, careful image handling, and performance budgets set before design began. The measurable goal was simple: pages usable on a mid-range phone over a weak connection. Design and development worked against that target together.

System integration across inherited tools

A company that had grown through acquisitions ended up with four systems that didn't share data.

We mapped what each one actually did, found two overlapping functions, and proposed a sequence: consolidate the overlap first, then connect the rest through a shared data layer. The work spanned several months and involved the client's IT team throughout. No single dramatic launch, just a steady reduction in manual data entry.

Early-stage products and MVP work

We work with founders who need a demo-ready product, often from incubator programs where the pressure is to show progress quickly.

Recent MVP builds followed a similar shape: a focused first release, a working prototype for demos, and a clear list of what comes next. We're direct about what an MVP can and can't prove. It shows whether people use the product, not whether the business scales.

What these examples have in common

None of them started with a technology choice. They started with a task that took too long, a system that couldn't talk to another system, or a process held together by one person's memory.

The build followed from there. If your project looks like one of these, or nothing like them, the next step is the same: describe the problem and we'll tell you what we'd do.

Describe your project See our services

Questions we get about project examples

Can you name the clients behind these projects?Details

Usually not. A large share of the work is confidential, which is why these entries describe the problem, the approach, and the build instead of naming companies or showing screens. When a client agrees to a public reference, we can talk about it in a call.

How long does a project like one of these take?Details

It depends on scope, and we won't quote a number before understanding the work. A focused MVP usually moves faster than a system integration that touches existing tools and other teams. After a short scoping conversation we can outline a realistic sequence and what has to happen first.

Do you only take on new builds?Details

No. Several of the examples above started from something that already existed: a spreadsheet, four inherited systems, a website that buckled under traffic. Fixing and connecting existing tools is often more useful than a rebuild, and we'll say so when it is.

What should I prepare before getting in touch?Details

A short description of the task that takes too long, the systems involved, and who on your side would work with us. You don't need a specification or a technology preference. Those come out of the conversation, not before it.

Two founders standing over a table in a fogged incubator workspace at night

Your project, described in your words

Send a few lines about the problem, the systems already in play, and who would work with us. We'll reply with what we'd do first and what we'd need to know before committing to a plan. If your situation doesn't match anything on this page, that's still a useful starting point.

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