Full-stack AI engineerHey, I'm Nicolai

I build AI that works outside the lab.

8+ years building AI products, and these days I build them end to end on my own: frontend, backend, AI, and the data plumbing. A lot of it now is putting an agent layer on top of the systems companies already run, with a clear estimate of what each one saves. I've worked with solo founders, startups, and enterprises, and I share what I learn with 126,000+ engineers on YouTube.

Nicolai Nielsen, AI engineer specializing in computer vision and production machine learning
Nicolai Nielsen · full-stack AI engineer
Building with AI8+ years
YouTube subscribers126K+
Technical videos400+
How I workSolo

Built with great teams

Solo founders · startups · enterprises

UltralyticsIUNO LAWNVIDIAICON BuildRoboflowForkliftNLTenyksDreamdazetekDataStax

Try it

What could AI do for your business?

Paste your website or drop in a photo from your business. Or tap an example to see what you get.

Paste your website. We'll read it and suggest where AI and computer vision could save you time, for your business specifically, not businesses in general.

Or see an example:

We only read public pages. The site address and the suggestions are kept so repeat scans are instant. Nothing about you is stored.

scan · yourcompany.comREADY
  • Reading your website
  • Working out what you do
  • Finding use cases
Waiting for a website0.0 s

The agent layer

Keep your systems. Add an agent layer on top.

Most of the value isn't a new app. It's letting AI agents safely do work inside the software you already pay for.

  1. 01

    Nothing gets replaced

    Your CRM, ERP, database, and internal APIs keep running exactly as they are. We build on top of them, not instead of them.

  2. 02

    A safe tool layer

    The actions your software already supports become tools agents can call, through MCP or plain APIs, with scoped permissions, validation, and a log of every call.

  3. 03

    Agents do the work, people approve

    Agents handle the repetitive steps across your systems. Anything that matters waits for a human yes.

  4. 04

    Any model, no lock-in

    Claude, GPT, Gemini, or open models. The layer stays the same when you switch.

Agents, a gateway, an integration layer, and your existing backend, untouched.
How we build agent layers

Active, not passive

Systems that act, and pay for themselves.

A dashboard someone has to read is a cost. The systems we build recommend the next step, or take it with your approval, and every one comes with an estimate of what it saves.

A passive systemAn active system
Shows a forklift came close to a person.Alerts the floor lead, logs the clip, and recommends a barrier at that crossing.
A dashboard with this week's jams.Spots the lane that jams most, tells the shift lead why, and creates the maintenance task.
An inbox of quote requests.Reads each one, prices it with your rules, and drafts the reply for a planner to approve.
A report of damaged pallets.Attaches photos to the shipment and drafts the claim to the carrier.
  1. 01

    Start from the cost

    Hours spent, errors made, claims lost, stops on the line. We measure today's number before building anything.

  2. 02

    Estimate before building

    A rough return for each idea up front, so you choose the ones worth doing first.

  3. 03

    Ship a small first version

    One camera, one inbox, one team. Real savings in weeks, not a year-long project.

  4. 04

    Measure what it saves

    Every action is logged, so the return is a number you can check, not a promise.

Live demos

Watch them work, or press a key.

Small working versions of the systems we build. They run on their own, and you can take over any time.

Fig 1Agent robot
CRMERPDOCS
Watch, or press a key
agent ready

AI integrations & agents

We turn the systems you already have, like your CRM, database, and internal APIs, into tools AI agents can use, with your approval where it matters.

Fig 2Inspection line
rundetectcount
Watch, or press a key
line stopped

Computer vision

Cameras that detect, count, and flag defects on real production lines, in real time. It's where NNCODE started.

Fig 3Sync hub
CRMERPDOCS
Watch, or press a key
0 of 3 sources

Full-stack apps & data

You tell us how you work. We connect your tools into one app and one source of truth: frontend, backend, and data.

Why I work solo

Why one person can beat a team.

Fewer people, fewer handoffs, and the person you talk to is the one building it.

You talk to me, not a chain of peopleWhen you message me, you're talking to the person actually writing the code. No account managers, no telephone game, no "let me check with the team".
No overlap, no back-and-forthPut five people on one product and a lot of the week goes into syncing, handing things over, and redoing each other's work. I hold the whole thing in my head, so that time goes into building instead.
AI agents do the heavy liftingAI coding agents write a lot of the code now, and they're fast. That means more people on a project often slows it down. My job is the architecture, the reviews, and the calls that need experience.
Cheaper than even one employeeCompared to hiring even a single full-time developer, you skip the recruiting, onboarding, benefits, and paying for quiet weeks. And instead of someone who covers one part of the stack, you get someone who covers all of it.
My full take on solo vs teams

A TYPICAL TEAM5 people · 10 lines to keep in sync

  • Meetings, tickets, and waiting on each other
  • Overlap and redoing each other's work
  • Bugs hiding in the gaps between people

ME + AI AGENTS1 person · 0 handoffs

Interface & UX
APIs & backend
AI & LLM integration
Data & integrations
Infra & deployment
NICOLAI + AI AGENTS
  • You talk directly to me
  • One way of building things, start to finish
  • New stuff to look at almost every day

Things we've built

Products, platforms, and real systems.

Open source used by engineers worldwide, products we run, and systems built for clients.

01 / 06

DATASET PLATFORM

Mask0

A private computer vision data platform for importing, annotating, validating, versioning, and exporting datasets without platform lock-in.

React · Python · PostgreSQL · Cloud deploymentVisit Mask0

About me

One person, the whole thing.

Interfaces, APIs, databases, data pipelines, LLMs, computer vision, and the servers it all runs on. I build every layer myself, which means it all fits together, and you always know who to talk to: me.

I also teach everything I learn. 400+ videos on machine learning, computer vision, LLMs, and shipping real projects. If you want to see how I think before we work together, that's the best place to start.

Nicolai Nielsen's AI and computer vision YouTube channel
4.2M+Channel views
2K+GitHub stars
100%Built by me

Let's talk

Got something you want to build?

Tell us about it. You talk directly with the person who builds it, from the first chat to everything after.

  • Reply within a day
  • Straight to the builders
  • No obligation