Services
MLOps and production ML
The unglamorous work that makes models real. Most machine learning dies after the prototype: no deployment path, no monitoring, no answer when the data drifts. We take models into production and keep them honest, with pipelines, monitoring, retraining and runbooks your engineers own.
What you get
- Deployment pipelines (CI/CD) for your models
- Monitoring and alerting on performance and drift
- Automated retraining with human sign-off
- Runbooks and handover so your team owns the estate
How it typically runs
Typical engagement: 8 to 16 weeks, 2 engineers, rolling retainer after go-live.
Every project is scoped individually. Book a discovery call and we will provide a detailed proposal within 48 hours.
Where it fits
This practice is delivered through one of the two QuantSpark engines.
Proof
MLOps and production ML in the field
27%
Data accuracy uplift · >1 FTE freed · £120k/yr saved
DataControl Platform: intelligent private equity data management
A mid-market private equity firm
Private EquityRead
65%
Less downtime
Predictive maintenance and ops dashboards for a UK industrial manufacturer
UK industrial manufacturer (£800m turnover)
Industrial & AviationRead
$30m
projected annual retention benefit
Predicting renewals and reducing churn at scale
Enterprise cyber security software provider
SaaS & TechRead