About NeuroSkill
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Who we are
Closing the gap between a working model and a team that trusts it
NeuroSkill was founded in 2019 by a group of data and platform engineers who kept being called in to rescue AI projects that had stalled somewhere between the demo and the day job. The pattern was always the same: a model that worked in a notebook, a business process nobody had redesigned around it, and a team that had never been shown how to use it. We built the practice to fix both halves at once — the system and the capability to run it.
Production, Not Prototypes
We only start building once the data, the reviewers and the success measure are in place. It is why 94% of what we pilot is still running a year later.
Handover You Can Rely On
Every engagement ends with runbooks, a model card, a monitoring dashboard and a trained internal owner. No dependency on us by design.
120+
Projects Delivered
64
Specialists On Staff
12k+
People Trained
40+
Client Organisations
Free readiness review
Forty-five minutes to a shortlist of AI use cases actually worth funding
Our approach
Two disciplines, one delivery team.
We staff engineers and enablement leads on the same team, working to the same delivery plan. The model and the people who depend on it mature together, so nothing is left stranded at go-live.
Engineering
Depth
Enablement
Built In
- Engineers and enablement leads staffed on the same team, from day one.
- We build inside your cloud tenancy, under your identity and retention rules.
- Nothing ships without a named internal owner trained to run it.
How we work
Two weeks to clarity, sixteen to production
Readiness Review
Two weeks mapping your data, your decisions and your risk appetite. You leave with a scored shortlist and a sequenced roadmap.
Build & Integrate
Eight to sixteen weeks building the model, the pipeline and the guardrails, deployed inside your environment and wired into the systems you already run.
Enable & Hand Over
Role-based training runs alongside delivery. By go-live your own people hold the runbook, the dashboard and the on-call rota.
Leadership
The people accountable for your engagement.
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Daniel Reyes
Founder & Chief Executive -
Elena Kovács
Head of Applied Machine Learning -
Marcus Lindqvist
Chief Technology Officer
Daniel Reyes
Founder & Chief ExecutiveDaniel spent eleven years leading data teams inside insurance and logistics operators before founding NeuroSkill. He sits in every readiness review personally.
Strategy & Readiness 95%
Client Delivery88%
Elena Kovács
Head of Applied Machine LearningElena leads model development and evaluation. Her rule for the practice: if a result cannot be reproduced from a versioned pipeline, it does not ship.
Applied Machine Learning 96%
Evaluation & MLOps90%
Marcus Lindqvist
Chief Technology OfficerMarcus owns platform, security and integration. He has taken machine learning systems through GDPR, HIPAA and financial services supervision.
Platform & Security 94%
Systems Integration86%
4.9
Average Client Rating
What we bring
Four things every engagement includes
Named Owner
A trained person inside your organisation who owns the system after we leave.
Model Card
Written record of what the model does, where it fails, and who reviewed it.
Live Monitoring
Drift detection and alerting your team reads, not a dashboard nobody opens.
Audit Trail
Every input, output and override logged and reportable to your regulator.
Client results
What changes after we hand it over
“We had two failed AI pilots behind us before NeuroSkill. They refused to start building until our data and our reviewers were ready. Submission triage now runs in hours, and our own team maintains it.”
“The forecasting model was the easy part. What changed our operation was the six weeks they spent with our depot planners, turning the output into something those planners would act on.”
“Clinical safety, information governance and a sceptical medical board — they handled all three without us having to translate. The documentation alone justified the engagement.”
“Three thousand four hundred people, nine months, and a measurable competency baseline at the end of it. Their enablement team knows the difference between training and theatre.”
