Founders / 0-to-1 Products

Workflow: One App on Web, iPhone, and Android

Before: Most teams would build and maintain three separate apps to reach web, iPhone, and Android. For one person that is not sustainable — but the app still had to feel right on every device.

Outcome: One build, used everywhere people already are. The beta has reached 1,000+ people across web, iPhone, and Android — no separate apps to maintain.

System: Qurannotate is built once and runs on the web, iPhone, and Android, with each version tuned to feel right on that device. People get the same capable app wherever they are. Paid monthly and yearly plans work across all three.

Workflow: Study Together Live, Even With No Internet

Before: Studying the Quran is something people do together — study circles, teachers and students, research groups. At the same time, people on weak or patchy connections cannot risk losing their notes when the signal drops.

Outcome: People study together with no fuss, and every note is safe no matter the connection. Anyone on a slow or spotty signal can work without worrying about losing their place.

System: Up to 30 people can write on the same Quran at once and see each other's cursors live, with no clashes when two people edit the same spot. If the internet drops, the app keeps working — your changes save on your device and sync the moment you are back online. Nothing is lost.

Workflow: AI Study Helper You Can Actually Trust

Before: Students and scholars need fast, reliable answers about Quranic Arabic, tafsir, and grammar. General AI tools make things up and can't point to real sources, so they can't be trusted for serious work.

Outcome: Get scholar-grade answers in seconds instead of hours of looking things up by hand. Because every answer shows its source, you can check it and trust it.

System: Ask about a word, its grammar, its tafsir, or where a topic shows up elsewhere, and get an answer drawn from a large library of trusted Islamic scholarship. Every answer comes with the exact source it's based on — and it won't answer without one. So unlike general AI, it doesn't make things up.

Workflow: Easy to Use, Easy to Find

Before: An app used by Arabic and English speakers around the world has to be easy to use, easy to understand, and easy to find. Most niche apps get none of these right.

Outcome: Arabic speakers get an app that reads the right way round. Everyone gets a product that's easy to use and well explained. The search articles keep pulling in new visitors over time.

System: The website has a help centre with 16 articles covering every main feature, full right-to-left Arabic support so it reads naturally, and accessibility checks that block any release that breaks them. 17 articles bring in new visitors from search. A desktop version is in the works but not out yet.

Workflow: Patient Records Built to NHS Standards

Before: Clinical software built on a sloppy records structure can't talk to NHS systems and won't pass review. Getting this right first is the hardest, most important call — fix it later and you rebuild everything.

Outcome: A records foundation that fits NHS systems and holds up under review — built once, correctly, before any screens. Everything else in FlapTrack is built on top of it.

System: Patient records covering the whole flap-surgery journey, built to the standard the NHS uses. Safety checks live inside the records themselves, so bad data can't sneak in. Each hospital only sees its own patients — that separation is locked in by the structure, not left to app code to remember.

Workflow: Automatic Red/Amber/Green Safety Alerts

Before: Deciding whether to call the surgeon now or wait can't hang on gut feel — that's inconsistent and slow. A safety call this important needs clear rules that always fire the same way and can't be talked out of.

Outcome: Safety alerts that fire the same way every time, leave a clear trail, and can be reviewed by a Clinical Safety Officer without reading any code.

System: Reads the bedside observations and gives a Red, Amber, or Green result using fixed safety rules — no guessing, no AI making it up. The same readings always give the same answer, and every alert scenario has a test proving it still works. The rules run on the server, so the result can't be faked or skipped from the app.

Workflow: Standard NHS Clinical Codes

Before: Clinical software that records conditions as free text can't connect to NHS systems or be searched properly, and it fails review. The codes have to go in while the records are designed, not bolted on later.

Outcome: Conditions are recorded in standard NHS codes, not loose text — so connecting to NHS systems and passing a safety review is a clear next step, not a rewrite.

System: Records flap-monitoring conditions using 157 codes from SNOMED CT, the standard NHS clinical terminology. Each code is tracked back to where it came from. They're candidate codes — unverified, awaiting Clinical Safety Officer sign-off before any clinical use — and the trail makes that review easy to follow.

Workflow: Clinical Homework & NHS Approval Plan

Before: Health software that doesn't understand the real clinical work, or have a plan for NHS approval, fails at the first review. That groundwork has to come before any product code.

Outcome: The clinical and approval groundwork is written down and checkable: it reflects real surgical practice, and the route to NHS approval is clear to reviewers, investors, and clinical partners.

System: Built on how 20 flap types are actually monitored across 3 specialties, grounded in 5+ peer-reviewed papers and NHS guidance, with 24+ rival systems studied. A plan maps out every NHS approval the product will need and where it stands on each — none earned yet, but the path is written down, not guessed.