[ Technology practice ]
From architecture to App Store, one team delivers web, native mobile, cloud, and applied AI - without the handoff gaps.
product engine4 surfaces1 intelligence layer∞ possibilities
Web, iOS, Android, and intelligent interfaces—designed as one connected experience.
A shared intelligence layer that helps every product understand, adapt, and improve.
We don't stop at ideas. We turn emerging technology into products people can actually use.
Imagine, prototype, ship, learn, repeat. The product is never finished—only getting smarter.
The practice funds its own products. Each one starts as a tool we needed and could not buy.
Chat, tasks, tickets, wiki and calendar as views over one object graph. Web, iOS and Android from a single codebase.
Meet DexterA living portrait of an organisation, drawn from the data it already produces rather than the deck it wrote about itself.
Ask about itSomething is being prototyped here. It gets a name when it survives contact with real usage.
[ A brief overview of Dexter ]
Dexter connects chat, projects, tickets and calendar in one workspace. A message becomes a task, the task moves the sprint, and the deadline lands on everyone's calendar.
Chat, tasks, files and calendar are views over the same object graph, not five products holding hands through integrations.
workspace └ object_graph ├ message → chat ├ task → board, sprint ├ ticket → queue ├ document → wiki └ event → calendar
Summaries render where the unread state lives. Commitments made in conversation become proposed tasks, with no chat window required.
Nothing auto-assigns silently. Every generated artifact is reviewable, and every summary links back to its source thread.
One shared UI and one backend across every platform your team works on, built with Kotlin Multiplatform and Compose.
Switch surface and watch which fields it actually reads. Nothing is copied between them.
We are a product engineering team, not a staffing desk. The same people who draw the architecture write the code, ship the build and hold the pager.
Production web applications in React and TypeScript. Real-time data, role-aware interfaces, and design systems built as tokens so the look survives the port to native.
Native iOS and Android, plus tablet, from a single Kotlin Multiplatform codebase. One shared UI, one backend, one design system across every device.
AI treated as a material, not a chatbot in the corner. Summarisation, extraction and drafting wired into the interface itself, proposing rather than committing, always traceable to a source.
Serverless backends on Firebase and Google Cloud: authentication, Firestore data modelling, Cloud Functions, storage, and migration paths for when the schema changes under live traffic.
Permission models resolved once at the data layer, not reconciled at four edges. Security rules, workspace isolation, server-side secret handling, and written threat models you can audit.
High and low level design, technical due diligence, and the unglamorous decisions that decide whether year two is cheap or expensive. Documented before implementation.
One team from architecture through handover, which is why the data model in the diagram is the data model in production.
[ In production ]
Everything here runs in something we ship. We pick tools that let a small team ship like a large one, and that a client's own engineers can pick up without a translator.
Four phases, run in the open. You see the architecture before the invoice, and a working build long before the launch date.
Audit the current stack, the workflows, and where the hours really go. We write down what we found, including the parts that argue against building anything.
artefact findings memo
High and low level design, data model, permission model, and a scope you can price. Decisions are documented so year two is not archaeology.
artefact HLD / LLD plus priced scope
Shipped in slices you can use, not milestones you can only read about. Design system, then screens, then the long tail, reviewed at every step.
artefact working builds on a schedule
Security rules, load behaviour, observability, and a handover your own team can actually own. Then we iterate on what real usage reveals.
artefact runbook plus handover session
Tell us what you are building, or what is currently held together with integrations and goodwill. We come back with an architecture, a scope and an honest opinion.