Case studies

The engineering, not the mood board.

EdgeBrain Studios is a software house in Lahore building production software for founders and lean product teams worldwide. The case studies below cover the three things we ship most: web applications on Next.js, cross-platform mobile apps, and AI automation that removes manual work rather than bolting a chatbot onto it.

Each one is written as an engineering narrative rather than a brochure. You get the constraint that shaped the architecture, the tradeoff we took, the part that turned out harder than we thought, and the numbers the build was measured against. If you’re shortlisting a development partner, that detail is what separates a real team from a folder of stock screenshots.

Five case studies, and every one of them is a real build. Two are our own products, Clora AI and Hush. Three were built for clients: Content Studio for Mindcob, and Fiona and the SEO Dashboard for clients who asked not to be named. Each card says which it is, and the study says it again. We’d rather show you the engineering honestly than assemble a logo wall.

Typical engagement: fixed scope, quoted before kickoff, four to eight weeks to production, working software in your hands every week. Senior engineers write the code and you talk to them directly.

How to read these

Five studies you can interrogate beats thirty tiles.

Five case studies is the entire portfolio, and that’s the honest number. EdgeBrain Studios is a young studio. We’d rather publish five builds you can take apart in a call than thirty thumbnails carrying a logo and an adjective. Two of them are products we own outright, Clora AI and Hush, which we can describe down to the render path. The other three we built for clients.

One of the three client builds names the client. Content Studio was built for Mindcob, who were happy to be named. The other two, Fiona and the SEO Dashboard, were built for clients who asked us not to name them, so those studies describe the system and stop there. That is the whole of it: we name a client when we have permission and we don’t when we don’t. If your shortlist turns on a wall of recognisable brands, we’re not the strongest name on it. Better learned here than on the second call.

What these studies are good for is the thing portfolios are usually worst at, which is showing how a team reasons once a constraint stops being negotiable. Four things each one puts on the record.

The constraint that shaped it

Every build is pinned to something a client cannot negotiate away, whether that is a device budget, a document format nobody controls, or a network that disappears for days. Each study names that constraint before anything else, because the decisions after it only make sense in its light.

The architecture decision

One or two choices decide how a project ages. Rendering strategy, sync model, where state lives, what the queue is for. We write down what we picked and what we turned down, so you can argue with the reasoning rather than take a screenshot on trust.

The tradeoff we accepted

Nothing is free. Offline-first buys reliability and charges you conflict resolution. An extraction pipeline buys hours back and charges you an evaluation set to maintain. Each study says what a choice cost as well as what it bought.

What it does not claim

No invented revenue lift. No conversion percentage we were never in a position to measure. No logo we lack permission to show. Where a client has asked not to be named, the card says only that it was built for a client, and the study holds the same line.

Ask us in the first call about the part where the reasoning turned out wrong. Each of these builds has one, and we’ll tell you which.

What we take on

Four kinds of problem, described by their shape.

The case studies above are five instances of the work below. If your project sits in one of these shapes, the service page carries the scope, the timeline, and where pricing starts.

Web

A product that survives real data and a mid-range phone

Marketing sites that load in under a second on a three-year-old Android. Dashboards that stay fast past the ten-thousandth row. Portals with auth, roles, and an admin screen nobody dreads opening. Next.js and TypeScript, deployed into your own cloud account.

Next.js web development scope, timeline, and pricing

Mobile

One codebase that behaves on both stores

React Native builds where offline is a designed feature rather than a bug report, sync is settled before the first screen is drawn, and app review rules are read in week one instead of discovered in week six.

React Native mobile app development scope and timeline

AI automation

Manual work you can point at

Document processing, extraction, classification, routing, ticket triage. If someone retypes the same thing dozens of times a week, that is the shape we automate. Accuracy gets measured field by field against your real documents before any of it reaches production.

AI automation for document and workflow processing

AI consulting

Deciding what is worth building at all

Sometimes the useful answer is that the model is not your bottleneck at all. We audit the workflow, price the options, and say which parts are worth automating this quarter, before anyone commits to a pipeline.

AI consulting for teams deciding what to build

Plenty of projects straddle two of these, and a few sit outside all four. If yours does, describe it in two paragraphs on the EdgeBrain Studios contact page and we’ll say which parts we’d take and who is better placed for the rest.

Your build is the next one written up.

Send us the problem in two paragraphs. You get a scope and a fixed price back, and no discovery invoice on the way there.

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