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Vessel Studio VESSEL STUDIO

AI & Technology Studio

We build AI systems that work in production.

Not prototypes. Not pilots. Software that ships, scales, and runs without intervention.

See our work Our story →

Trusted by teams at

Anthropic Anthropic
GitHub GitHub
Vercel Vercel
Stripe Stripe
Linear Linear
Supabase Supabase

Selected work

All case studies →
Predictive Analytics

Arc Systems — Customer Intelligence Platform

View case study →
Computer Vision

Forma Labs — Design Intelligence Layer

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AI Infrastructure

Meridian Financial — Risk Modeling Platform

View case study →

What we build

Work at the intersection of intelligence and production software.

01

Custom AI Systems

Trained models, inference pipelines, and agentic frameworks built to your domain. We go further than off-the-shelf.

02

Production Engineering

The work after the model: APIs, queues, monitoring, failover. Systems that stay running at 3am.

03

Data Architecture

Clean pipelines from source to insight. Schema design, warehouse strategy, real-time and batch.

04

LLM Integration

Embedding frontier models into workflows that already exist. Careful, reversible, auditable.

05

Model Fine-tuning

Domain-specific adaptation. Your data, your constraints, your accuracy requirements.

06

AI Strategy

For leadership teams: what is actually feasible, what it costs, what order to build it in.

How we work

A process built for results, not comfort.

  1. 01

    Discovery

    One structured call. We learn the problem, the constraints, the team, and what done looks like. No retainer, no ambiguity.

  2. 02

    Architecture

    We design the system before we write code. You see the plan, you approve it. Nothing starts until you do.

  3. 03

    Build

    Iterative delivery. Weekly demos. You see the system grow in real time — no big reveal at the end.

  4. 04

    Handover

    Documented. Tested. Yours. We stay involved until you can run it without us, then we let go.

Evidence, not claims

94%

Model accuracy

Average across client deployments

11

Days to prototype

Brief to deployed working system

4

Enterprise clients

Running in production today

0

Data incidents

Since 2021

“

They delivered a fraud-detection model that we actually trust. The explainability work alone was worth the contract. Every assumption documented, every edge case covered.

Kwame Asante — Head of Risk, Meridian Financial

“Vessel rewired how we think about product data. The pipeline they built runs 400k events a day without intervention. We haven’t touched it in eight months.”

Yuki Tanaka — VP Engineering, Forma Labs

“I’ve worked with three AI vendors. Vessel are the only ones who told us what wouldn’t work before they started billing. That honesty is rare and worth paying for.”

Marcus Webb — CTO, Arc Systems

Pricing

Transparent pricing. No hourly surprises.

Every engagement is scoped and priced upfront. You know the number before we start.

Discovery

For teams who need clarity before committing. A structured audit with a written architecture recommendation.

$2,500 one-time
  • 2-day intensive workshop
  • Competitive landscape review
  • Data audit and gap analysis
  • Written architecture brief
  • Prioritised build roadmap
Book a discovery

Most popular

Build

From brief to production. A complete engagement — model, infrastructure, documentation, and handover.

$15,000 per project
  • Full system design and review
  • Model training and evaluation
  • Production API and deployment
  • Monitoring and alerting setup
  • Handover documentation
  • 30-day post-launch support
Start a project

Retainer

Ongoing embedded partnership. For teams who want senior AI engineering without a full-time hire.

$5,000 per month
  • 40 hours per month
  • Dedicated Slack channel
  • Weekly strategy call
  • Priority response SLA
  • Quarterly architecture review
  • Rollover hours (up to 20)
Enquire about retainer

FAQ

Questions we get asked.

What makes you different from an AI agency or consultancy?
We build software, not decks. We take projects from brief to production and stay involved until the system runs without us. We do not outsource the engineering.
How long does a typical engagement take?
Most first projects run six to ten weeks — two weeks scoping, four to six weeks build, one week handover. Ongoing retainers are available after the first project.
Do you sign NDAs and work under confidentiality?
Yes, always. We have a standard NDA we can turn around quickly, or we can work with yours. Client confidentiality is non-negotiable.
Can you work with our existing stack?
Almost certainly. We work primarily in Python, and have production experience with most major cloud providers, data warehouses, and ML serving infrastructure. We adapt to your environment rather than forcing ours on you.
Do you take equity instead of cash?
Occasionally, for the right company at the right stage. This is something we discuss during discovery. We have taken small equity positions in three clients — all of whom we would have taken as cash clients anyway.
From the blog All posts →
Engineering

Why we use TypeScript for every AI integration we build

Read → Systems

Building reliable LLM pipelines: eleven systems, one lesson

Read →

Start a conversation

Ready to build something that works?

We take on three to five new clients per quarter. Tell us what you’re trying to solve.

Get in touch