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.
We bring product thinking and engineering together, so structure, UI, APIs, and the launch checklist live in one plan.
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. You see progress on the critical path every week.
- 02
Design
System design, AI/tool boundaries, interface direction, and interaction prototypes. Nothing here waits on a handover between separate teams.
- 03
Build
Modern stack, clean architecture, evaluated AI behavior, and iterative demos you can react to. On AI development projects we favour practical architecture over trendy defaults.
- 04
Launch
Ship, monitor, harden, and keep improving models, tools, and product after go-live. The work for teams in New York stays tied to the outcome you asked for.
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 New York
Same timezone and a face to meet, which genuinely matters for some teams. You are also paying New York companies hiring on portfolio proof and production AI. 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
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
CRM Dashboard
Frontend · Analytics
Customer relationship dashboard with management workflows and data visualization on Next.js.
Freelance CRM surface for managing relationships and visualizing key metrics, deployed on Vercel.
- · CRM management views
- · Data visualization
- · Responsive dashboard layout
- · Vercel deployment
Next.js · React · Tailwind · Vercel
Working with teams in New York
New York companies hiring on portfolio proof and production AI. We work with clients in New York remotely and keep overlapping hours in EST/EDT. We usually collaborate in English.
How we work with New York teams
New York is on ET, so our afternoon covers your morning. In practice that means a scheduled daily window for anything that needs a conversation, and written updates waiting when you start.
What New York clients usually need
New York briefs cluster around fintech, media, and B2B SaaS. A lot of the work is replacing a prototype that got a company to revenue but cannot carry the next stage of growth.
Contracts, data, and compliance
Contracts are usually US contractor agreements with IP assignment and an NDA. Fintech projects get SOC 2 evidence and audit logging scoped into the build rather than retrofitted before a raise.
