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AI Decision Intelligence Solutions
Move from dashboards to clear next-best-action recommendations delivered inside your team's workflow.
Service
Intelligent Decision Making
Best for
High-volume operational decisions (pricing, routing, allocation) where even a 1-3% lift compounds into significant margin.
Signature outcome
A real-time dispatch engine that cut SLA breaches by 38% across 12 regions.
Overview
Most companies are not short of dashboards. They are short of decisions. A dashboard describes what happened and leaves a human to work out what to do; a decision system recommends the specific action, in the moment it is needed, in the tool where the work happens.
We build that layer by combining forecasting with optimisation: predict demand, risk, churn or cost, then translate the prediction into a concrete recommendation on pricing, routing, allocation or intervention. Every recommendation carries a short explanation of why it was made, and every time someone overrides it we capture that, because override patterns are the fastest signal of where the model is wrong.
It pays off wherever the same decision is made hundreds or thousands of times a week and a small percentage improvement compounds: pricing desks, dispatch and scheduling, inventory allocation, credit and risk, retention offers. The engagement starts by picking one decision, measuring how it is made today, and agreeing the number that has to move.
How we approach it
Most companies have dashboards that describe what happened. We build systems that recommend what to do next. By combining forecasting, optimization, and continuous learning, we surface the best pricing, routing, allocation, or intervention decision directly inside the tool your team uses (Salesforce, SAP, or a custom console). Every recommendation is explainable, and every override is captured to make the system smarter over time.
Business questions we answer
“Where are your teams making high-volume decisions that a smarter, data-driven suggestion could improve?”
What you get
- Forecasting and recommendation models tailored to your data
- Real-time recommendations delivered inside your existing tools
- Clear explanations behind every suggestion
- Override tracking to measure trust and improve accuracy
- Continuous retraining as your business evolves
Frequently asked
AI Decision Intelligence Solutions: common questions
What is decision intelligence?
Decision intelligence combines forecasting, optimisation and business rules to recommend a specific action rather than just report a metric. The output is a next-best-action delivered into an operational workflow, with an explanation and a record of whether the human accepted it.
How is this different from our BI dashboards?
BI is descriptive: it shows what happened. A decision system is prescriptive: given the current state, it recommends the action with the best expected outcome and measures whether that outcome occurred. The two are complementary; the decision layer usually reads from the same warehouse.
Will our team trust automated recommendations?
Only if they can see the reasoning and keep control. We ship recommendations with plain-language explanations, allow overrides by default, and start in advisory mode. Automation increases only after the accepted-recommendation rate proves the system is right more often than not.
Where do the recommendations appear?
Inside the system your team already uses, whether that is Salesforce, SAP, a dispatch console or an internal tool. Adoption collapses when people have to open a separate application to see the suggestion.
How long before we see measurable impact?
A first decision use case typically runs a supervised pilot at 10 to 12 weeks, with measurable impact over the following quarter once enough decisions have gone through it to be statistically meaningful.
Proof in production
Relevant case studies
Let’s solve your data challenge