Product development · AI features & integration
AI features inside mobile and web apps — LLM integrations, assistants, agents and automation — from a team that ships AI in its own products.
AI app development at Digital Services means adding AI where it does a real job inside a mobile or web product — LLM-powered features, in-app assistants, agents and workflow automation, and vision features like Bazarly's photo-to-listing — built with the same AI-accelerated engineering process we use on our own apps.
Most "AI-powered" labels describe a chatbot bolted onto the side of a product. The useful version is narrower: find the one step in a user's journey that is slow, repetitive or easy to get wrong, and let a model do the first draft of it. In Bazarly, that step was writing a listing — so a seller photographs the item and AI suggests the title, category and description, which they edit and post. The user stays in control; the blank form disappears.
We build that kind of feature into client products: LLM integrations that summarise, classify, extract or draft; in-app assistants grounded in the product's own content; agents and automations that carry out multi-step work behind the scenes; and vision features that turn a photo into structured data. Each one is designed around its failure mode — what the app does when the model is wrong, slow or unavailable — because that is what separates a feature people trust from a demo.
The same tools change how we build. Our engineering process is AI-accelerated: AI coding and agent tools help draft, test and refactor, while the decisions that matter — architecture, data handling, review and release — stay with engineers. It is the process behind our own four apps, and the one a client project runs on.
- AI feature discovery — where a model genuinely saves your users effort, and where it doesn't
- LLM integrations that summarise, classify, extract and draft inside your app
- In-app assistants grounded in your product's own content and data
- Agents and workflow automation for multi-step tasks
- Vision features that turn a photo into structured data, like Bazarly's photo-to-listing
- Fallbacks, guardrails, cost controls and privacy handling around every AI call
Questions
About ai app development.
Can you add AI features to an app that already exists?
Usually, yes. Most AI features sit behind a call from the existing app to a back-end service, so they can be added without rebuilding the product. The real scoping question is where in the user's journey a model actually saves effort.
Which AI models do you use?
We choose per feature rather than committing to one provider. The right model depends on the task, the latency the screen can tolerate, cost per call and where the data is allowed to go — and the integration is built so the model can be swapped later.
What does AI-accelerated engineering mean?
AI coding and agent tools are part of our day-to-day build process — drafting code, tests and refactors — while engineers own architecture, review and release. It is how we build our own apps as well as client projects.
Do your own products use AI?
Yes. Bazarly's AI photo-to-listing suggests a title, category and description from a seller's photos, which the seller can edit before posting. It is included in the white-label version of Bazarly that businesses license.
Other capabilities in product development
UI/UX Design
Customer journeys, information architecture and UI/UX for mobile apps, web apps and digital products.
Read more 02Mobile App Development
Native and cross-platform mobile apps, web applications, APIs and the back-end that holds them up.
Read more 03App Store Launch
Store submission, review, release management and the support that keeps a live product healthy.
Read more 04SEO, AEO & GEO
SEO, app store optimisation, answer-engine visibility and campaigns that bring people to the thing you built.
Read moreReady to talk about ai app development?
Send a paragraph on what you're building — that's enough to start scoping.