[glossary]

Terms we use

Plain definitions, in the order you are likely to meet them.

Accelerator

Prebuilt, reusable IP — code, models, templates, and process — that shortens the path from idea to production for a recurring problem.

Agent

An AI system that takes actions, calls tools, and makes a sequence of decisions to complete a task, rather than returning a single prediction.

AI Agent Ops

The discipline of running agents in production: evaluation sets, observability, guardrails, release process, and ownership.

Control

A group or baseline that continues with the existing process so that uplift from an AI system can be measured rather than assumed.

Customer 360

A single, governed view of each customer assembled from fragmented sources, with an identity key, attributes, and features ready for activation.

Decision intelligence

Predictive modelling, optimisation, and next-best-action services wired into the point where decisions are made.

Find. Prove. Build. Scale.

LoxiLabs' engagement journey: locate value, test the workflow with real users and data, set production foundations, extend the outcome.

Kill criterion

The pre-agreed result at which an initiative is stopped. Makes a fast, cheap no a legitimate outcome.

Missing layer

The connection between AI strategy and product design, data and workflow adoption, and the economics required to scale — where most AI value is lost.

Operating model

Who decides, who builds, who runs, and who pays for AI in an organisation, and the governance that ties them together.

Pilot metrics

Technical measures such as accuracy, recall, and latency. Inputs to a decision, never the headline result.

P&L impact

Change in revenue, margin, cost, or risk that the business already reports. The measure every LoxiLabs engagement is judged on.

Production readiness

Architecture, governance, and unit economics defined before a prototype is shown as a demo.

Synthetic segmentation

Modelling and segmenting a market using synthetic populations built from public, licensed, and first-party signals, where first-party data is thin.

Unit economics

Cost per outcome — inference, licences, data, and people — at the volume production will see.

Ready to move from pilots to P&L?

Tell us about the decision or workflow you want to change. We'll come back with an honest view on whether it's worth proving, and what it would take.

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