Generative AI App Development · Canada

Generative AI products and copilots, engineered for production

We design, build and ship LLM-powered applications end to end: product thinking, UX, backend, model integration, evaluation and deployment. We run two AI products of our own, so we know what it takes to keep one working after launch.

Why it matters

Why generative ai app development needs more than a demo

The gap between a promising prototype and a dependable product is mostly engineering: streaming UIs, structured outputs, retries and fallbacks, prompt versioning, evaluation, rate limits, cost tracking, privacy and security review. Skipping it is why so many AI pilots never make it to production.

What you get

  • Product and technical design
  • Production web, mobile or API application
  • Evaluation harness and monitoring
  • Documentation and handover, or ongoing support

What we deliver

Our generative ai app development services

AI features in existing products

Summaries, smart search, drafting, classification and assistants added to your web or mobile app without rebuilding it.

Copilots and internal assistants

Role-specific assistants for analysts, agents, support staff and engineers, connected to the systems they already use.

Prompt and model engineering

Versioned prompt systems, structured JSON outputs, model routing between fast and capable models, and caching to keep latency and cost down.

Evaluation and quality loops

Golden datasets, automated scoring, user feedback capture and regression testing so quality is measured, not guessed.

Full-stack delivery

React and Next.js front ends, Python and Node back ends, Postgres and pgvector, Firebase, and cloud deployment on GCP, AWS, Azure or Vercel.

Security and privacy review

Prompt-injection defences, data-handling reviews, PII redaction, key management and tenant isolation designed in from the start.

Use cases

Where teams use it

  • Analyst copilots for research, filings and market data
  • Sales and agent enablement tools with calculators, scripts and objection handling
  • Customer-facing assistants for product questions and onboarding
  • AI writing, summarization and translation features in SaaS products
  • Voice and text-to-speech features using on-device models
Why RAG demos break on real documents, and how Akurion handles itNarrated explainer that starts with why RAG prototypes fail on large, changing document sets, then shows Akurion product screens: connectors, auto-generated metadata keys, chat filters, the Graph RAG relationship map, cited source pages opened in chat and the MCP playground.

Kitchener · Waterloo · Cambridge · Guelph

Generative AI development in Kitchener-Waterloo

We build generative AI products and features for Waterloo Region start-ups and established companies alike, and can work alongside your in-house developers in Kitchener, Waterloo or remotely.

Service area

Waterloo Region: Kitchener, Waterloo, Cambridge, Guelph, Elmira, St. Jacobs, New Hamburg, Baden, Ayr, Wellesley, Breslau

Nearby, in person: Stratford, Brantford, Hamilton, London, Woodstock, Milton, Toronto and the GTA

Remote: everywhere in Canada, including Ottawa, Montreal, Calgary, Edmonton, Vancouver and Halifax

Process

How a project runs

  1. 01

    Discover

    We map the workflow with the people who run it, find the highest-value automation points and agree measurable success criteria.

  2. 02

    Prototype

    A working prototype on your real data in weeks, not months, tested with real users against the agreed criteria.

  3. 03

    Harden

    Security review, evaluation suite, monitoring, permissions and integration with your systems, ready for production.

  4. 04

    Run and improve

    We hand over with documentation and training, or stay on to operate, measure and extend the system.

Generative AI App Development: frequently asked questions

How long does it take to build a generative AI app?

A focused prototype on real data usually takes a few weeks. A production release depends on integrations, security review and scope. We agree acceptance criteria up front so progress is measurable.

Do you only build chatbots?

No. Chat is one interface. Many of the most useful AI features are invisible: classification, extraction, routing, drafting and summarization inside a workflow your team already uses.

Can you work with our in-house developers?

Yes. We can lead the build, pair with your team, or set up the architecture and evaluation framework and hand it over.

Do you work with Kitchener-Waterloo start-ups?

Yes. We help start-ups add AI features, build MVPs and set up evaluation and deployment, either leading the build or working with the in-house team.

Tell us about the process you want to automate.

A 30-minute call is enough to tell whether AI is a fit, what a first project would look like and what it would take to run it in production.