AI engineering for real business outcomes
Plenty of agencies are built around long retainers. What you actually want is a live site, an app in the stores, and users adopting it.
Design and engineering share one backlog, so the visuals never drift away from what can realistically ship on time.
If that sounds like your situation, Arcode is set up for businesses searching for an AI agency. Agents, RAG, MCP, and LLM features delivered as working systems rather than slide decks.
What you get
- AI strategy to implementation
- Agent and MCP builds
- Knowledge systems
- Automation that sticks
- One studio accountable for the result
- Design and engineering on the same schedule
- Support available after launch
How engagement works
As your AI agency, we run a shared backlog, design reviews, and engineering sprints, and you keep one point of contact throughout.
- 01
Discover
Goals, constraints, data sources, and success metrics, all settled before we touch architecture or prompts. The work for teams in Toronto stays tied to the outcome you asked for.
- 02
Design
System design, AI/tool boundaries, interface direction, and interaction prototypes. You see progress on the critical path every week.
- 03
Build
Modern stack, clean architecture, evaluated AI behavior, and iterative demos you can react to. Nothing here waits on a handover between separate teams.
- 04
Launch
Ship, monitor, harden, and keep improving models, tools, and product after go-live. On AI development projects we favour practical architecture over trendy defaults.
How we build it, and why
The stack is chosen per project, not applied from a template. For AI agency work these are the defaults, and the reason each one is on the list.
- OpenAI
- a second model provider, so a single vendor's outage or price change is not your problem
- Claude
- long-context reasoning and reliable tool calling for agent work
- MCP
- the Model Context Protocol, so your tools plug into Claude, Cursor, and other agent clients without a custom adapter for each
- RAG
- retrieval over your own documents, so answers cite your data instead of the model's training set
- Next.js
- server rendering and static generation in one framework, so marketing pages stay fast and app routes stay dynamic
What the first weeks look like
- Week 1
Scope and architecture
Users, data, integrations, and constraints, ending in a written plan for the AI development that you approve before anyone opens an editor.
- Weeks 2-3
Design the critical path
The screens that carry the product, prototyped and clickable. Design and engineering review together, so nothing gets drawn that cannot ship.
- Weeks 4-8
Build in weekly slices
Every week ends with something on a real URL. ai strategy to implementation lands early, because the rest of the plan depends on it working.
- Launch
Ship, measure, hand over
Release, monitoring, analytics, and a documented handover, so your team can carry it without calling us.
Weighing up your options
There are three realistic ways to get this built. Each is the right answer for someone.
A solo freelancer
Cheapest per hour and fine for a contained task. The risk on AI development is breadth — one person covering design, backend, infrastructure, and launch usually means one of them is weak, and there is no cover when they are unavailable.
A local agency in Toronto
Same timezone and a face to meet, which genuinely matters for some teams. You are also paying Toronto startups seeking remote product delivery partners. rates for the whole team including the layers that never touch your AI development, and a local shortlist is a small shortlist.
Arcode
A small senior team. The people who scope the AI development write the code, you get weekly demos instead of status decks, and the engagement ends when the thing is live and handed over.
Work we have shipped
Case Management Hub
Full-stack engineer · NestJS · Next.js
HIPAA-compliant healthcare SaaS for 150+ US organizations, with dual databases, realtime collaboration, billing, and secure client portals.
Enterprise case management platform for healthcare and social-work organizations with encryption, realtime messaging, Stripe billing, Zoom, and calendar sync.
- · HIPAA-ready architecture with encryption and audit logging
- · Realtime collaboration via Socket.io + Redis
- · Client portal and role-based access control
- · Stripe billing and document workflows
Next.js · NestJS · TypeScript · MongoDB · Redis · Socket.io
Note Assist
AI product · Next.js · Speech
AI meeting assistant with live speech-to-text, ChatGPT chat, and Firebase auth for transcription workflows.
Freelance AI product built with Next.js, Firebase, AssemblyAI, and ChatGPT for live meeting transcription and realtime chat around the transcript.
- · Live speech-to-text transcription
- · Realtime chat over meeting notes
- · Firebase authentication
- · AI-assisted follow-up on transcripts
Next.js · Firebase · AssemblyAI · ChatGPT · TypeScript
Brain CMS
Frontend · Firebase · Analytics
Multi-module enterprise CMS with documents, calendars, video, and advanced analytics.
Content and operations system spanning enterprise modules with Firebase and rich media tooling.
- · Multi-module business domains
- · PDF and document management
- · Advanced charting suites
- · Calendar and media workflows
React · Redux Saga · Firebase · Chart.js · Video.js
Working with teams in Toronto
Toronto startups seeking remote product delivery partners. We work with clients in Toronto remotely and keep overlapping hours in EST/EDT. We usually collaborate in English.
How we work with Toronto teams
Toronto is on ET, giving us an afternoon-to-morning overlap. That supports a daily call window plus asynchronous updates for everything that does not need one.
What Toronto clients usually need
Toronto briefs are mostly B2B SaaS and internal platforms, often from teams with product sense but no in-house engineering capacity to build what they have specified.
Contracts, data, and compliance
We invoice in CAD or USD. PIPEDA obligations and Canadian data residency come up regularly, so we confirm hosting regions and data flows before writing code.
