Probabl Support · For ML team leads

Expert predictive modeling support, from the people behind scikit-learn.

Reduce technical debt. Secure your production pipelines. Get a trusted escalation path, backed by the maintainers themselves.

200M+scikit-learn monthly downloads
48hresponse-time SLA
1.xscikit-learn maintained line
The risk you're carrying

ML pipelines don't fail loudly. They erode quietly.

The real risk isn't a single bug. It's the slow accumulation of fragile pipelines, inconsistent practices, and decisions that work for now because only a few people understand them.

Discuss your ML risks with an expert →
  • 01Unclear best practices for predictive modeling pipelines
  • 02Inconsistent preprocessing, validation, and feature handling
  • 03Models that are hard to maintain or upgrade over time
  • 04Surprising behavior or performance regressions
  • 05Knowledge concentrated in a handful of contributors
  • 06No trusted escalation when decisions are ambiguous or high-stakes
Is this for your team?

More predictable systems. Shared standards. Less key-person risk.

Probabl Support is ongoing expert back-up, not one-off consulting. You keep ownership; we provide escalation, guidance, and shared standards, including edge cases most teams hit alone.

Edge-case expertise
  • Causal inference
  • Explainability
  • Survival analysis
  • Calibration
  • Imbalanced data
  • Time-series CV
  • Drift & monitoring
  • Probabilistic forecasting
Good fit
  • Own, ideate and produce predictive modeling systems and are accountable for results, reliability and continuity
  • Need a trusted and rapid escalation path for ML issues
  • Want to upskill the team without outsourcing ownership
  • Need an expert ML sparring partner
Not a fit
Operating model & plans

Ongoing expert back-up. Not one-off consulting.

You keep ownership of your ML systems. We provide the escalation path, the standards, and the maintainers, so your team can ship with confidence.

How teams choose

Essential for fast answers. Growth for shared standards. Scale for long-term ownership.

★ Most chosen
Essential Data Science Helpdesk

Fast answers, when you need them.

Growth Best Practices + Expert Back-up

Shared standards across the team.

Scale Full Lifecycle Expert Capacity

Long-term partnership across the lifecycle.

Helpdesk
Centralized ML helpdesk
Response-time SLA (48h)
Escalation to scikit-learn maintainers
Incident management
Use case confidentiality
Best practices
Best practices library
Masterclass seats, 20% discount
Dedicated masterclass
Expert consulting
Expert consulting hours
Up to 5h / month
Up to 10h / month
Lifecycle coverage
Ideation, Experimentation
Full lifecycle (incl. Deployment & Monitoring)
Design review, observations, implementation
Governance
Quarterly roadmap review
Dedicated account manager
Optional add-on
scikit-learn.org ecosystem visibility
On demand
On demand
On demand
Frequently asked

Answers, not deflections.

Is this generic ML support?
No. This support is rooted in predictive modeling as designed and implemented in scikit-learn. The maintainers and core contributors are the ones answering tickets, not a tier-1 support team reading from a runbook.
Do you replace internal teams?
No. We extend and upskill them. You keep ownership of your ML systems and decisions; we provide an escalation path, shared standards, and a sparring partner for the hard calls.
Is this consulting?
No. This is ongoing expert back-up and knowledge transfer. We don't take ownership of your roadmap or your code, we make your team better at owning theirs.
How fast do you respond?
Within 48h on the response-time SLA, on every plan. For incident management on Growth and Scale, we triage faster, typically within hours during European working time.
Can we keep our use cases confidential?
Yes. Use case confidentiality is included on every plan; nothing leaves your environment without your sign-off, and we work under the NDA you provide.
What is the difference vs. Forward Deployed Engineer?
FDE is for teams who want ML work fully delivered: we embed and ship. Support is for teams who already ship, and want a trusted maintainer on call. Many customers use both.

Ready to talk to a maintainer? Start the conversation.

Discuss scikit-learn support →