run
Operate and improve your systems and teams over time.
Your AI systems are in production. But a model in production without supervision is a ticking time bomb. We handle the operation, monitoring and continuous improvement of your Data and AI applications so they remain high-performing, reliable and compliant over time.
+150 companies supported
— 5/5 on Google
Challenges
The challenges you face
Your AI systems are in production but no one supervises them. Models drift, performance degrades and your teams don't have the bandwidth to maintain what's running.
01
No one is monitoring your models in production.
The model was delivered 18 months ago. Since then, the data has changed, performance has degraded and no one has noticed. Decisions based on this model are no longer reliable.
02
Your teams don't have the bandwidth to maintain AI systems.
Your Data Scientists want to work on new projects, not maintain old ones. Your IT teams know how to manage traditional applications, but not ML pipelines and drifting models.
03
One model incident and it's panic.
The pricing model crashes on a Friday night. The data pipeline stops running. No one knows who to call or where to look. No procedure, no on-call duty, no plan B.
04
Your AI systems stagnate instead of improving.
The model has been doing the same job since it went into production. No retraining, no optimization, no adaptation to new data. The value created at launch erodes month after month.
Our answer
Our approach
We work both as advisors and on structured projects, with a commitment to results.
Scoping and audit of existing systems
We audit all your AI systems in production: model status, pipeline quality, infrastructure, documentation, existing alerts. We identify immediate risks and areas for improvement.
Monitoring setup
We deploy a complete monitoring system: model drift, incoming data quality, latency, error rates and automatic alerts. You know in real time whether your AI systems are working as expected.
Ongoing operations and maintenance
Our team runs your systems day to day: incident management, bug fixes, model retraining when performance shifts and data pipeline updates.
Optimization and continuous improvement
We don't just maintain. Every month, we analyze performance and propose optimizations: model improvements, infrastructure cost reductions, new features. Your AI systems gain value over time, not the other way around.
Benefits / Impact
What you gain
AI systems that stay reliable over time, performance that improves instead of stagnating and Data Scientists freed up to innovate.
01
AI systems that stay reliable over time. Monitoring detects drift before it impacts your operations.
We deploy a complete monitoring system: model drift, incoming data quality, latency and error rates. You know in real time whether your systems are working as expected, before your users find out at your expense.
02
Operational peace of mind. Incident management, on-call duty, escalation: you have a dedicated team that knows how to step in when something breaks, without tying up your in-house teams.
A model that crashes on a Friday night, a pipeline that stops running: we have the procedures, on-call rotations and SLA levels suited to the criticality of each system. Your IT teams don't get woken up in the middle of the night.
03
Performance that improves instead of stagnating. Regular model retraining, continuous optimization and integration of new data so the value created grows quarter after quarter.
We don't just maintain. Every month, we analyze performance and propose optimizations: model improvements, new features, threshold adjustments. Your AI systems gain value over time, not the other way around.
04
Controlled infrastructure costs. We optimize cloud resources and pipelines to keep your infrastructure bill from soaring as data volumes grow.
Instance rightsizing, query optimization, cleanup of unused resources: we treat infrastructure as a cost item to be managed, not an invisible expense that silently drifts.
05
Your Data Scientists freed up to innovate. They focus on new use cases instead of spending their time debugging old ones.
Maintaining systems in production is a full-time job that your most qualified people shouldn't be doing. We take over operations so your Data team can focus on what creates the most value: the next projects.
Your questions, our answers
All the answers to understand our approach, how we work and what you can expect from working with us.
What does the Run phase involve at Diametral?
The Run phase operates and improves your AI systems in production over time. Diametral handles day-to-day operations, monitoring, incident management and continuous improvement, through a monthly or annual contract with contractual SLAs and monthly business performance reporting.
What is model drift and how do you detect it?
Model drift is the gradual degradation of an AI model when production data moves away from training data. Diametral detects drift through continuous monitoring of distributions, performance and user feedback, with automated alerts and a retraining protocol triggered as soon as a critical threshold is crossed.
Why maintain AI in production?
An unsupervised AI model is a ticking time bomb: its performance silently degrades, its predictions drift and the decisions it feeds become hazardous. Diametral's Run phase ensures the reliability, compliance and evolution of the system in the face of business, regulatory or technological change.
What SLAs does Diametral offer in the Run phase?
Diametral offers SLAs tailored to the criticality of each system: detection time, incident resolution time, availability, drift threshold and reporting frequency. Commitments are contractually agreed upfront and reported monthly via a dashboard shared with your business and IT leadership.
How can you optimize the costs of AI in production?
FinOps optimization of AI in production involves adjusting compute, rationalizing model calls and automating the shutdown of unused resources. Diametral carries out an initial FinOps audit and then applies continuous optimizations, with a typical 20% to 40% reduction in the AI cloud bill over the first few months.
contact
Your AI systems deserve better than autopilot.
Describe your scope. A Diametral expert will work with you to assess the right operating model.