Since 2014
Make the right AI bet.
Take it to production.
We find where AI creates real business value, then design, build and run production systems around your data, workflows and existing stack. Built so your own team can own them.
2014
In production since
80+
AI systems shipped
610M
Inferences in 2025
11
Countries
New · 2026
AI technology partner, Meridian Digital Hub
Read the announcement →
Trusted by teams across Europe and the US
Kavo
Lumen
Orbital
Fieldnote
Parcel/9
Halden
Mosswood
01
The problem
Most AI never
leaves the demo.
Not because the model fails. Because production is a different job. Here is where it breaks, and what we do instead.
01
The use case isn’t worth it
We validate value and feasibility before any code.
02
The data isn’t ready
We build on the data you actually have, not the data you wish you had.
03
Strategy gets handed off
One senior team, from the first decision to deployment.
04
It never meets real traffic
Latency, cost and monitoring are designed in from day one.
7/10
AI pilots we audit have no path to production. The cause is rarely the model.
Sable field notes · 2026
02
Decision · Plan
Many ideas.
One right bet.
The biggest AI risk is not bad code. It is the wrong problem. We are the consultancy that builds what it recommends, so the advice has to survive production.
Discovery Sprint
Half a day · use cases and fit
€1,200
Strategy Blueprint
2 days · roadmap and business case
€6,000
03
Architecture · Build
Structure
before scale.
Custom models, agents and the data infrastructure behind them, designed around real data, integrations, latency, cost and maintainability. Whatever the problem needs, not whatever is trending.
01
Custom AI systems
Built around your challenge, data and stack.
02
AI agents
Reason, act and integrate, with production controls.
03
Data & ML engineering
Pipelines and ML infrastructure that stay reliable.
04
Computer vision
Detection, search and inspection on real-world images.
05
Language models
Retrieval, extraction and assistants with evaluation built in.
06
Search & recommenders
Discovery for catalogues with millions of items.
Proven components:
Auto-tagging
Visual search
Anomaly detection
Duplicate detection
Recommenders
04
Production · Scale
Running.
Every day.
Model inferences served in 2025
Built to be owned. Senior engineers stay close as the system grows, and your team gets the model, the docs and the ability to retrain it.
240M
Images processed
130 TB
Data under management
21
Systems shipped in 2025
05
Proof
Not demos.
Systems in production.
Lumen Health
Live
A triage assistant for 300 clinics,
from hours to minutes.
Retrieval over clinical guidelines with human sign-off on every answer, deployed inside the clinics’ existing ticketing tool.
STACK
PyTorch · pgvector · Triton
Orbital Freight
Live
Route prediction across nine ports,
live on every dispatcher screen.
A forecasting service that learns from ten years of port calls and pushes predictions straight into the dispatch board.
OUTCOME
18% fewer empty miles
06
Trust
Built before
the hype.
A team shipping machine learning since 2014, published research in visual search, and a seat where the rules for AI in the region are written.
Meridian Digital Hub · AI technology partner
Since 2026
European Applied AI Network
Board member
AI regulation working group
Committee
Applied ML Summit 2026
Programme chair
“Deep technical judgement, honest about what will not work, and a system our own team now runs.”
07
Where to start
Two ways in.
Fixed price to start.
Not sure where AI fits?
Find the right AI bet.
Discovery Sprint
Half a day · use cases and fit
€1,200
Strategy Blueprint
2 days · roadmap and business case
€6,000
Have a pilot that has to go live?
Take it to production.
Production Review
Senior review of what you already have
€2,400
Production Pilot
About 4 weeks · built to go live
from €18k
Agentic AI Workshop. Two 4-hour sessions: use-case validation, architecture and a go / no-go for your highest-priority agent.
€5,500 fixed
01
What does Sable actually do?
We are a senior AI engineering and consultancy partner. We help you choose where AI pays off, then design, build and run the system around your data, workflows and stack.
02
Do you build custom models or use existing ones?
03
Can you work with our existing systems?
Next
Your pipeline
Bring us the
business problem.
We’ll tell you whether AI is the right move, and what it would take to make it work in production.