Solutions · AI-First Web Apps

Web apps where AI is the point, not the gimmick

Most enterprise software is a forms-and-tables shell over a database. The AI revolution is rebuilding that shell so it adapts to the user, surfaces the right information at the right moment, and removes the busywork (data entry, classification, summarisation) that the old version forced humans to do.

We build web apps with that AI layer designed in from day one, not bolted on as an afterthought.

What it actually does

An AI-first web app is a custom application built around your specific workflow, with frontier-model intelligence embedded in the parts that actually need it. Instead of a generic CRUD interface, the app handles tasks the user would otherwise do manually: drafting documents, classifying inputs, extracting structure from unstructured content, summarising long records, recommending actions.

We take the same approach to product design as a SaaS company would: clean component-driven UI, real-time updates where they matter, mobile-responsive by default, production-grade authentication and security. The difference is the intelligence layer. AI capability sits inside the workflow, not as a chat sidebar bolted on the edge.

Common patterns we build: internal admin consoles for operations teams, customer-facing portals with smart assistants, document-heavy back-office workflows where extraction and routing eat the most time, and replacement/extension of legacy line-of-business tools that your team is sick of.

How it works

The shape of a typical build. Yours will vary on the specifics, but the pattern is consistent.

Step 1

Workflow mapping

We shadow the team currently doing the work, map every step, and identify which moments have AI leverage (drafting, classifying, extracting, summarising) versus which are pure data plumbing.

Step 2

Architecture and stack choice

We pick the frontend framework (usually Next.js), database (Postgres via Supabase or your existing), AI provider per workflow, and deploy target (your cloud or ours). All decisions explained, no black-box choices.

Step 3

Build with the AI baked in

Each AI-enabled feature is built with proper evaluation: structured outputs, confidence scoring, fallback paths. The UI surfaces uncertainty appropriately so users can trust the parts that work and override the parts that don't.

Step 4

Integrate with your existing stack

Single sign-on (Microsoft, Google), data sync to/from your CRM and other systems of record, webhook handling for upstream events. The new app fits into your existing flow, doesn't replace it.

Step 5

Ship and iterate

Pilot rollout to a small user group first, structured feedback for two weeks, then full rollout. Hosting, monitoring, error tracking, and support handover packaged with the build.

This fits if you...

Have a team currently using spreadsheets, email, and one or two SaaS tools held together with copy-paste, and the friction is real.
Need a custom workflow that off-the-shelf SaaS doesn't quite cover (the 'we tried five products and none of them fit' situation).
Want to embed AI into specific moments of an existing operation, not replace the whole thing.
Have data already (in your CRM, in spreadsheets, in PDFs) that an AI could read and act on.

This isn't a fit if...

Your needs are 100% covered by a major SaaS product. Buying beats building when an existing tool genuinely fits.
You want a generic 'add ChatGPT to our website' chat widget. We don't build those; you can deploy one yourself in an afternoon.
Your operation is too small to justify a custom build. The lower bound is roughly 5+ active users; below that, off-the-shelf is almost always cheaper.

Typical build shape

Scope

One core workflow built end-to-end as a working web app: auth, database, frontend, AI features, key integrations, deployment.

Timeline

Roughly 2-3 months for a focused first version. Subsequent features added in shorter increments.

Indicative price

Fixed-price build, scoped to the workflow and integrations. Ongoing maintenance and feature work runs as a monthly retainer.

All ranges in NZD ex-GST. Precise numbers come out of the operations audit. See our engagement model for the full pricing approach.

Often paired with

Related capabilities

Intelligent CRMs Mobile Apps AI Project Management

See if it fits your operation

30-minute discovery call, no pitch. We tell you whether this capability solves your actual bottleneck or whether something else (or nothing) would work better.