Services/Data and AI
Data and AI
Decisions with a source
Pipelines, warehouses, governance, analytics, machine learning, and generative AI that is allowed to touch production only after the data is fit for it.
Data engineering
Reliable pipelines into a warehouse or lakehouse. Late files, bad keys, and silent failures are treated as defects.
Analytics and BI
The few reports leaders open, built on definitions finance and operations both accept. Self-serve where it helps, curated where it must.
Data governance
Ownership, quality, catalog, and access. Governance as a working practice, not a committee that meets quarterly and changes nothing.
Machine learning
Models for a decision you already make badly or slowly: forecast, classify, detect, rank. With monitoring, because a model left alone decays.
Generative AI
Assistants and generation inside a real workflow, with retrieval, evaluation, and a rule for what the model is not allowed to do.
Agentic systems
Software that takes multi-step actions — with tools, permissions, and a human on the steps that can spend money or mail a customer.
AI agents
Agents that finish a bounded job across your systems. Tools, a written autonomy line, a registry entry, and a person who can stop the run.
Decision intelligence
Forecasts, scenarios, and optimization wired into planning — supply, workforce, pricing, credit — where a better number changes a meeting.
Sustainability data
Emissions, energy, and supplier data collected with the same discipline as finance data, so a disclosure is not a three-month scavenger hunt.