Vancouver Web Design

Production AI - 18+ years of agency craft

Custom AI That Actually Ships

We don't pitch AI roadmaps - we ship them. Eight live AI applications in production across paving, restaurant equipment, content moderation, and enterprise document discovery. See what we've built. Then let's build yours.

Book a DemoSee our work

Trusted by Canadian businesses since 2007

World Health OrganizationLMS Reinforcing Steel GroupFraserway RVABC RecyclingITC

What we've built

Six Ways We Put
AI to Work

Each card is a service we've shipped in production. Click through to see the work, the tech, and the build approach.

AI Surface Renderer

Swap the material on a specific surface. Pixel-accurate. Driveways, floors, walls, countertops.

SAM3AI RENDERINGMATERIAL SWAP
Read more →

AI Scene Editor

Redesign parts of the scene. AI decides what to change. Lawns, landscapes, outdoor spaces.

GPT-4o VisionGPT-IMAGE-1INPAINTING

AI Document Parser & Auto-Importer

AI agents parse unstructured PDFs, structure the data, and auto-import to Shopify, Magento, and more.

MULTI-AGENTPDF PARSINGHITLAUTO IMPORT

AI Content Moderation

Image and video moderation at scale. Flags what breaks your rules before it goes live.

AWS REKOGNITIONIMAGE & VIDEOAUTO-FLAGGING

Enterprise Document Discovery

Citation-grade answers from your own document library. A 173-PDF corpus ingested in a single RAG.

RAGEMBEDDINGSCITATIONS

Customer & Team Chatbots

Secure chatbots connected to your business data. 24/7 for customers, instant answers for staff — on-prem when data can't leave.

GPT-4oOLLAMAON-PREM

AI in production, by the numbers

0

Multi-PDF corpus, citation-grade retrieval

0+

PDF-to-structured-data pipeline

00

Vision, document AI, RAG, moderation & more

00 Days

Average across active deployments

Production-grade stack

From cloud to edge — we run AI three ways.

We choose tools to match the problem, not hype. OpenAI for multi-agent vision flows, image generation, and chatbot orchestration. AWS Rekognition for image and video moderation. Ollama when sensitive data must stay on-prem. Meta SAM + Stable Diffusion for surface rendering. Self-hosted, cloud, or in-browser — three deployment modes, one accountable team.

OpenAI GPT-4oAnthropic ClaudeGeminiQwen 2.5OpenAI GPT-4oAnthropic ClaudeGeminiQwen 2.5
GeminiQwen 2.5OpenAI GPT-4oAnthropic ClaudeGeminiQwen 2.5OpenAI GPT-4oAnthropic Claude

Why choose us

Why Teams Choose
Nirvana for AI

Cloud, self-hosted, or in-browser — your choice

We run AI three ways: cloud API for speed, self-hosted on your own servers for data sovereignty, and client-side in the browser for instant performance. Most agencies only do one.

A full-stack agency, not a one-trick AI shop

18 years of web, design, and marketing craft behind every AI build. The same team that ships your AI tool also designs the UI, builds the CRM, and runs the SEO. Fewer vendors. One accountable partner.

Production-tested. SR&ED-defensible

Every AI we ship is built to operate, monitor, and document for the long term. Our content moderation work has been claimed under SR&ED. We write the kind of code your auditor approves of.

AI workflow visualization

How we work

A Milestone Centric AI Build

Every AI project follows the same four phases, with sign-off and visibility at every gate.

1

Technical Discovery & Feasibility

We map your data, your existing systems, and your business goal. You leave with a written feasibility brief, a model/tech stack recommendation, and a fixed scope for Phase 2.

2

Roadmap & Milestones

We split the build into milestones, each with a demo. You see working software at every gate. No 12-week silence followed by a surprise.

3

Development & Testing

Iterative builds with weekly demos. Real users in the loop from week 3. We measure latency, accuracy, and cost as we build, not after.

4

Deployment & Integration

We deploy to your cloud, your hardware, or ours. We integrate with your CRM, ERP, or Shopify. We hand you the runbook. We stay on retainer.

Where we ship

Industries We Ship AI For

We've shipped production AI in nine verticals and counting. The same agentic patterns adapt across industries — only the data changes.

Home & Trade Services

Home & Trade Services

Restaurant & Hospitality Equipment

Restaurant & Hospitality Equipment

E-commerce & Retail

E-commerce & Retail

Coupons, Loyalty & Cashback

Coupons, Loyalty & Cashback

Frequently asked questions

The Questions We Get Most

How do you decide which AI model to use for my project?
We start with your problem, not the model. GPT-4o for vision + structured JSON output. Anthropic Claude for nuanced classification or long-context reasoning. Gemini for fast image edits. Self-hosted Ollama with qwen2.5 when your data can't leave your server. We pilot 2-3 options in Phase 1 of every project and pick based on accuracy, latency, and cost on your real data.
Can you build AI that runs on our own servers — not in the cloud?
Yes — it's one of three ways we deploy. Cloud API when you want the strongest models and fastest iteration. Self-hosted on your own hardware (Ollama running open models like qwen2.5) when your data can't leave your building. In-browser when you need instant, zero-server-cost inference. We recommend one in the Phase 1 feasibility brief based on your data sensitivity, latency needs, and budget.
Will our data be used to train someone else's model?
No. When we use cloud APIs, we use business-tier agreements where your data is not used for training. When that's not enough, we run the model on your servers, so nothing leaves your infrastructure at all. Either way, your data stays yours: we minimize what's sent to any model, and we document exactly what flows where so your compliance team can verify it.
How much does a custom AI project cost?
It's phased, so you never bet the budget on an unknown. Phase 1 is a fixed-price discovery: you get a feasibility brief, a model recommendation, and a fixed scope for the build. The build is split into milestones, each priced and each ending in a working demo. We also measure inference cost per request as we build — so you know the monthly running cost before launch, not after the first invoice.
How long before we see something working?
Weeks, not quarters. Every milestone ends with a demo of working software, and we put real users in front of the build from week 3. There's no 12-week silence followed by a big reveal — you watch accuracy, latency, and cost improve gate by gate, and you can stop or redirect at any milestone.
What happens when the AI gets something wrong?
We design for it from day one, because every model is sometimes wrong. High-stakes outputs go through human-in-the-loop review — our document parser flags low-confidence extractions for a person instead of guessing. Our RAG systems cite their sources so every answer is checkable. And we measure accuracy on your real data during the build, so you know the error rate — and the safety net around it — before going live.
Who maintains the system after launch?
We do — we stay on retainer for monitoring, fixes, and model upgrades, which matters in a field where a better, cheaper model ships every few months. Prefer to own it in-house? We hand over the runbook, the monitoring setup, and documentation written to SR&ED standards — your team (and your auditor) can pick it up without us.

GET IN TOUCH

have an idea?
LET’S BRING IT TO LIFE.

Services Required*