Machine Learning & Decision Intelligence

Turn data into always-on intelligence with production-grade ML and analytics.

We build modern data foundations, predictive models, and decision intelligence products that give your teams trusted insights at speed.

Book a data strategy review Explore engagement tracks
↑4x experiment throughput
↓30% time-to-insight
95% data trust scores

Included in every engagement

  • • Business value hypothesis and measurement framework
  • • Data platform architecture, governance, and MLOps
  • • Experimentation, enablement, and operational playbooks

Engagement tracks to move from insight to impact

Start with strategic direction, accelerate delivery, or scale operations—we meet you where you are.

Design your roadmap
Insight accelerator

Data & ML strategy sprint

Align business priorities, data readiness, and governance for ML and analytics programmes.

  • • Value prioritisation & KPI scorecards
  • • Data platform & governance blueprint
  • • Use-case portfolio and roadmap
Duration: 3–4 weeks
Build sprint

Model & product delivery

Ship predictive, forecasting, or optimisation models with human-centered decision design.

  • • Feature engineering & model experimentation
  • • Decision UX, explainability, and storytelling
  • • Deployment with CI/CD and data contracts
Duration: 6–10 weeks
Operate & optimise

MLOps & analytics ops

Keep models and dashboards reliable with continuous evaluation, retraining, and adoption programmes.

  • • Monitoring, drift detection, and alerting
  • • Retraining pipelines & governance cadences
  • • Analytics enablement & change management
Retainer: Quarterly or annual

Data and ML capabilities end-to-end

Multidisciplinary teams blend data strategy, engineering, science, and storytelling to drive adoption.

Meet the team

Data foundations

  • • Lakehouse, mesh, & modern warehouse patterns
  • • Data governance, quality, and metadata
  • • Real-time ingestion & CDC pipelines

Model engineering

  • • Forecasting, optimisation, and personalization
  • • Computer vision, NLP, and graph analytics
  • • Explainability, fairness, and bias mitigation

Decision products

  • • Scenario simulators & recommendation engines
  • • Embedded analytics & insight experiences
  • • KPI storytelling & adoption programmes

Operations

  • • MLOps pipelines, versioning, & observability
  • • Data reliability engineering and runbooks
  • • Enablement for analysts, product, and ops teams

Measured outcomes

We bake metrics and instrumentation into every initiative from day one.

↓ 40%

Inventory holding costs reduced through demand forecasting and replenishment automation.

↑ 2.5x

Increase in marketing ROI by unifying attribution and predictive audience modelling.

↑ 35%

Higher conversion rates enabled by personalised product and pricing recommendations.

↓ 55%

Reduction in analytics backlog thanks to governed self-service dashboards and data products.

Our delivery approach

A repeatable, transparent cadence to unlock trust in data and ML.

01

Discover & align

Stakeholder alignment, value mapping, and data readiness assessment with governance milestones.

02

Build & validate

Model experimentation, human-centred insight design, and iterative validations with business teams.

03

Operate & evolve

Monitoring, retraining, and enablement programmes to institutionalise data-driven decision making.

Accelerators & artefacts

  • • Reusable feature store templates and data contracts
  • • Experiment tracking, evaluation, and model cards
  • • Governance playbooks for ethics, bias, and compliance
  • • Adoption toolkits and literacy programmes

Ecosystem expertise

We partner with leading cloud, data, and ML platforms across industries.

Snowflake
Databricks
BigQuery
AWS SageMaker
Azure ML
Vertex AI
dbt
Airflow
Power BI

Build intelligence into every decision

Tell us about your data ambitions—we’ll craft a roadmap that unites strategy, engineering, and adoption.

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