MLOps & AI Platform Engineering
MLOps consulting services
The unglamorous layer that decides whether your models survive contact with production.
A model that cannot be retrained, versioned, rolled back, or explained is a liability with good accuracy numbers. Our MLOps consulting builds the platform underneath your models: reproducible training, a registry, evaluation gates, and drift monitoring.
What this covers
- Model registry and reproducible training pipelines with full lineage
- CI/CD for models - automated evaluation gates before production
- Drift, quality, and cost monitoring on live inference traffic
- Feature stores and serving infrastructure sized to actual load
How we engage
- Audit how models currently reach production and where the manual steps hide
- Stand up the registry, pipelines, and evaluation gates around your existing work
- Hand over a platform your ML engineers own, with runbooks for the failure modes
More in AI & Data Intelligence
Most engagements draw on more than one capability, built as a single stack rather than separate practices.
- AI & Data ScienceFrom a question nobody can answer to a model in production answering it.
- Machine Learning EngineeringModel development that survives contact with real data.
- Computer VisionTeaching a camera to catch what a person would miss on the tenth pass.
- Natural Language ProcessingStructure out of the text nobody has time to read.
- Generative AILLM systems that answer from your data, not the model's guess.
- Agentic AIAutonomous agents for the decisions that are routine, not the ones that aren't.
- Recommendation SystemsThe right item in front of the right person, measured, not guessed.
- Data Wrangling & Feature EngineeringThe unglamorous 80% of a model's performance nobody budgets for.
- Data Engineering & Systems IntegrationTrustworthy data, and systems that were never designed to talk actually talking.
Common questions about MLOps & AI Platform Engineering
Can't find what you're looking for? Ask us
Do we need a data platform in place before we can do AI?
Not a finished one, but you need the feeds the model depends on to be reliable. Data engineering and MLOps are capabilities inside this pillar precisely because most stalled AI programmes are actually stalled data programmes - we build the two together rather than waiting on one.
Ready to talk through your next move?
Book a 30-minute strategy session with a ECLACTRA™ lead - no sales deck, just a straight conversation about where AI, geospatial, engineering, or fractional leadership could actually move the needle.