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AI Accelerators · Your AI partners

AI adoption, fast-tracked. 10+ accelerators, ready to deploy.

Most AI programs stall between the demo and the P&L. We are your AI partners across that distance: we pick the use cases worth building, deploy proven accelerators on your data, and drive adoption across the organization until the impact shows up in the numbers.

0 ready accelerators · proven in deployment, live on your data in weeks
2-6% of food cost taken out by hourly demand forecasting alone
5-20% basket-size lift from recommendations at the point of order
2 weeks from prioritization sprint to a scored, sequenced deployment plan
How we partner

Four moves, from ambition to adoption.

Business-first, not tech-first: every move is anchored to revenue, cost or customer experience, with leadership sponsorship treated as a precondition, not an afterthought.

1
Calibrate the architecture Security, accuracy and cost are decided by the architecture, not the demo. We set the enterprise AI stack up to scale before the first use case ships.
2
Prioritize the use cases Every candidate scored on impact, feasibility and time-to-value, and the workflow redesigned around it, so AI changes the work, not just the tooling.
3
Build adoption, org-wide Role-based AI fluency, change champions and adoption targets tracked like any other KPI, because unused AI has an ROI of zero.
4
Co-deliver to the P&L We implement with your internal and external teams, pilot to scale, accountable to the impact number, not the go-live date.
Ready to deploy

The accelerators, with the numbers attached.

Built and proven in QSR, our deepest library, and re-tuned for FMCG, logistics, healthcare and financial services on the same architecture. The ranges below are what these use cases typically move.

Marketing · ML

Store network optimization

Geo-AI on demand pockets and competition decides where to open, and where to close.

20-40% better capital allocation on the network
Marketing · ML

Dynamic menu & pricing

Prices and featured items follow demand, inventory, weather and time of day, automatically.

2-5% revenue uplift, at current volumes
Customer · ML

Recommendation engine

The right add-on, combo or pairing, surfaced at the moment of order, on every channel.

5-20% basket-size lift
Customer · ML

Customer lifecycle management

Predicts who will lapse and who will upgrade, and triggers the retention play in time.

3-7% churn reduction
Operations · ML

Hourly demand forecasting

Order volumes by hour and SKU drive prep, staffing and inventory decisions.

2-6% food cost down · 1-3% revenue up
Operations · ML

Labor forecasting & scheduling

The right staff by hour and role: rosters built within demand, skills and labor-law limits.

8-15% labor-productivity improvement
People · ML

CV matching

Candidates filtered on skill, experience and pay expectations, in minutes, not weeks.

50-70% less screening time
People · ML

Attrition prediction

Flags who is at risk of leaving, and why, while there is still time to act.

20-30% fewer unplanned exits
Risk · ML

Procurement fraud detection

Anomalies in pricing, vendor behaviour and purchase orders, flagged as they happen.

1-3% procurement leakage recovered
Risk · Computer vision

Store fraud detection

Void fraud, discount misuse and refund manipulation caught at the counter.

0.5-2% revenue leakage recovered
Finance · ML

Store profitability AI

Predicts unit-level margin and names the actions that improve it.

3-8% margin improvement per store
Finance · Agentic

Automated FP&A

MIS, variance analysis and forecasts produced by agents, reviewed by your team.

30-50% reporting cycle-time reduction

Which accelerator pays best in your business?

A two-week prioritization sprint scores the candidates on impact, feasibility and time-to-value, and answers with numbers, not slideware.

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