Project delivery
A defined scope, timeline and price. Best for new products, MVPs and well-understood builds. Weekly demos, milestone payments.
Mobile apps, web platforms, SaaS, AI, cloud and design, delivered by the engineers who built and still operate the MCQsLearn ecosystem. Eight service lines, one standard: software that works in production, not just in a demo.
Native-quality iOS and Android apps built on a shared code base, from a single-purpose utility to a flagship with subscriptions, offline content and gamified engagement.
We have shipped 55 apps to the App Store and Google Play and kept them updated for five years. That experience shapes everything: how we structure code so one team can maintain dozens of apps, how we design onboarding so users reach value in their first session, and how we handle store review, privacy labels and age ratings without delays.
Fast, secure web applications such as learning portals, dashboards, admin systems, customer-facing products, engineered to hold up under real traffic and real data volumes.
Our own platforms serve tens of thousands of content pages and quizzes to students in 150+ countries. We bring the same discipline to client work: clean APIs, sensible state management, accessibility by default and performance budgets we actually measure.
Corporate, product and content websites that load fast, rank well and convert, with search-engine structure designed in from the first wireframe.
Multi-tenant SaaS platforms with subscriptions, billing, roles and analytics, architected so onboarding your hundredth customer is as smooth as your first.
We run subscription products ourselves, so we design for the whole lifecycle: trial → conversion → retention → expansion. That means usage metering, plan management and admin tooling are planned from the start, not bolted on later.
Practical AI that measurably improves outcomes: adaptive assessment, LLM-powered tutors and assistants, recommendation systems and workflow automation.
Our own roadmap is built around AI that understands each learner (see Our Goal). For clients, we focus on the unglamorous parts that make AI features succeed in production: data pipelines, evaluation, guardrails, cost control and explainability.
Research-led product design: user flows, wireframes, design systems and high-fidelity prototypes tested with real users before a line of code is written.
Secure, cost-aware cloud architecture on AWS: serverless back-ends, containers, CI/CD, monitoring, and a migration path that gets you there without downtime.
Bespoke systems for workflows off-the-shelf software can't handle: LMS integrations, assessment engines, content pipelines, internal tools and APIs built around how your organisation actually works.
How to work with us
A defined scope, timeline and price. Best for new products, MVPs and well-understood builds. Weekly demos, milestone payments.
Engineers, designers and QA embedded with your team on a monthly basis. Best for evolving products and long roadmaps.
Architecture reviews, AWS cost audits, app-store readiness and AI feasibility studies. Short, focused engagements with written recommendations.
How we work
Six stages, no surprises. You see progress every week and own every deliverable.
Goals, users, constraints and success metrics, captured by our requirement engineers.
Product roadmap, technical approach, timeline and a transparent estimate.
Flows, wireframes, design system and clickable prototypes validated with users.
Agile sprints with weekly demos, code reviews and continuous integration.
Functional, performance and device testing, then store submission and release.
Monitoring, updates, analytics and a roadmap for what comes next.
Technology
We pick technology for maintainability and fit, and we'll tell you when the boring option is the right one.
Questions
Next step
Send a short description and we'll come back with questions, an approach and a realistic estimate, usually within two business days.