AI-Native Web & Mobile App Development
The products are designed with a focus on AI from the very beginning, all the way from the minimum viable product to full-scale deployment. A single team is responsible for developing both the app and the intelligence within it—following specifications, accelerating development with the use of agents, and being built with what AI products truly require: evaluations, latency budgets, and token economics.
When AI-native engineering is the right answer
The AI is the product; you'll need a team that views models, evaluations, and user experience as part of a single system—not one that simply adds an API call on top.
There is a 'magic' button which users attempted once. AI-native involves reworking the workflow in light of the intelligence, not merely decorating the existing one.
You should have a real MVP within weeks—something that is production quality, not just a prototype that you'll end up rewriting.
What we build
AI-first product design
Workflows designed around what models are genuinely capable of, including their failure states, feedback loops, and trust signals — the things that determine whether AI products succeed or fail.
Full-stack web applications
Web applications that are modern and have AI at their core are responsive, fast, and designed with iteration in mind as the models improve.
Mobile applications
iOS and Android apps that use both on-device and cloud-based AI, designed with real-world network conditions and latency in mind.
AI feature engineering
The features relating to copilots, semantic search, personalization, and generation are included in your current product and are made available behind flags with quality being measured.
Spec-driven MVP sprints
Taking an idea and turning it into a working, production-ready MVP by using the SoftmaxAI Method — with an approved specification initially and then weekly demonstrations.
Scale & cost engineering
The token budgets, caching mechanism, model routing, and cloud architecture have all been optimized so that the unit economics can sustain your growth.
Where this earns its keep.
Every engagement runs spec-first, agent-accelerated, human-owned.
A written specification that has been approved by the client prior to any coding taking place — covering the architecture, the edge cases, and the acceptance criteria.
The engineers arrange for the AI agents to carry out the specification in parallel, taking weeks rather than quarters.
The evaluations, tests, and security checks are carried out together with the build, and humans examine every decision that is important.
The system has been deployed to your GCP or AWS, complete with monitoring, production evaluations, and retraining loops.
From the portfolio.
Automatic video metadata that creators can rely on
Production-quality AI incorporated into a media platform's product to automatically convert video content into summaries, titles, and timestamped chapters, thereby enabling creators to spend less time on manual cataloguing.
Tools we reach for.
Chosen for each project based on evaluations and fit — never out of habit.
Questions, answered.
What makes an app "AI-native" rather than an app with AI features?
How fast can you ship an MVP?
Do you handle design and UX too?
Who owns the code?
Can you take over or upgrade an existing app?
Have a use case in mind? Let's pressure-test it — free.
A 30-minute call with our engineers, not a salesperson. You'll receive an honest assessment of feasibility, a preliminary architecture, and a clear next step.
Book a free AI consultation