AI & Data Science
AI and data science consulting
From a question nobody can answer to a model in production answering it.
Most AI programs stall between the pilot that impressed everyone and the system anyone actually uses. Our AI and data science consulting covers both halves - the statistical work to prove a model earns its place, and the engineering to put it somewhere it changes a decision.
What this covers
- Predictive modelling and forecasting built to a defined decision
- Experiment design and honest evaluation - baselines, holdouts, error analysis
- Statistical consulting on which method actually fits the data you have
- Decision-support interfaces, so the output reaches the person who acts on it
How we engage
- Frame the decision the model is meant to change, and how you will know it did
- Prototype against real data, with a baseline to beat and a go/no-go threshold
- Ship to production, instrument it, and train your team to run it
More in AI & Data Intelligence
Most engagements draw on more than one capability, built as a single stack rather than separate practices.
- 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.
- MLOps & AI Platform EngineeringThe unglamorous layer that decides whether your models survive contact with production.
Common questions about AI & Data Science
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.