New: Read our 2026 AI Implementation Playbook →

Service

AI Implementation.

We build and deploy the AI system. You get working software — not slides, not a POC, not a prototype that dies in a drawer.

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From $15,000 CAD · Fixed-scope sprints · Canadian team

What We Build

Production AI, end to end.

We've shipped AI systems for SMBs since 2018 — starting with Messenger chatbots, now building Claude agents, GPT-4o integrations, RAG pipelines, and full-stack automation. What we build works in production, handles real users, and doesn't fall over when the edge cases show up.

AI agents that take action — not just answer questions

RAG systems grounded in your company's knowledge base

Customer-facing chatbots that hand off gracefully to humans

Internal automation that eliminates repetitive ops work

AI pipelines that connect your existing stack end to end

Every project includes

Working software

Production-ready code, not prototypes. Delivered to your repo or hosted environment.

Data pipeline

Clean connectors to your existing systems — CRM, ERP, databases, APIs.

Safety & guardrails

Prompt engineering, output validation, and fallback logic so the AI behaves.

Test suite

Automated tests covering the critical paths. You'll know when something breaks.

CI/CD setup

Automated deployment pipeline so updates ship safely without babysitting.

Team handoff

Documentation and a live walkthrough so your team can own and maintain the system.

The Stack

Tools we actually use.

We pick the right tool for the job — not whatever we get paid to recommend.

Anthropic Claude

Sonnet 4, Opus 4 — for reasoning, writing, and complex agent tasks

OpenAI GPT-4o

For multimodal input and high-volume classification tasks

LangChain / custom agents

Multi-step agentic workflows and tool-use orchestration

Pinecone / pgvector

RAG pipelines that ground answers in your company's knowledge

Next.js / FastAPI

Production web layers — REST, WebSocket, SSE streaming

n8n / Make

Rapid automation glue when custom code isn't the right answer

Timeline

6 weeks to production.

Most projects. Complex integrations may run 8–10 weeks.

1

Week 1

Spec & design

Align on scope, pick the stack, design the data flow, lock the success criteria.

2

Week 2–3

Core build

Build the main AI loop, data connectors, prompt chain, and API layer.

3

Week 4

Integration & testing

Connect to your production systems, run edge cases, tune prompts.

4

Week 5

Staging deploy

Soft launch in your staging environment. Internal users test against real data.

5

Week 6

Go live

Production deploy, monitoring wired up, team trained, support window open.

Common questions.

What's the minimum project size?

Our minimum engagement is $15,000 CAD. Most projects run $15k–$75k depending on complexity and integrations.

Do you work with our existing tech team?

Yes. We can embed as extension of your team, hand off cleanly to your devs, or manage the full build. Your call.

What if requirements change mid-project?

We use fixed-scope sprints. Changes are scoped and priced before work starts — no surprise bills.

What happens after launch?

We offer a 30-day support window after go-live. For ongoing support and iteration, we can move to a retainer.

Do you use offshore developers?

No. All work is done by our team in Canada.

What AI models do you use?

Primarily Claude (Anthropic) and GPT-4o (OpenAI). We're model-agnostic — we pick what fits the task, not what we're partnered with.

Ready to build something real?

Tell us what you want to automate or build. We'll tell you if it's worth doing and what it will cost.

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