Names anonymized where engagements are active. Numbers real. Sample from 52 live opportunities in our pipeline across banking, retail, construction, real estate, telecom, and insurance.
12-month AI transformation roadmap for a commercial bank with 500+ employees and 300,000+ retail customers. Every major operational friction point — mapped, prioritized, and solved.
60–70% of 15–25k monthly calls were simple questions stealing time from complex cases.
3–7 days per application. 25–40% of applicants dropped off to competitors.
30–40% of staff time on manual KYC, AML, and regulatory reporting.
€500k–2M in annual fraud losses caught after the fact.
Conversational AI across web, app, WhatsApp, and voice. Handles 60–70% of queries autonomously.
From 3–7 days to 15–30 minutes for 70% of cases. Analysts focus on edge cases only.
KYC onboarding from 2 days to 30 minutes. Compliance reports from 5 days to 4 hours.
Transactions scored in milliseconds. 70–80% fraud prevention.
30+ store chain with €100M+ annual revenue. Food waste was eating 5–8% of revenue. Stockouts cost another 8–12%. We built the forecasting and inventory engines that ended both.
5–8% of gross revenue lost to expiry. €5M+ annually.
Based on previous weeks only — ignoring weather, holidays, events.
8–12% out-of-stock on high-demand products = €3M lost revenue.
Points-based, no personalization, no recommendations. 2–3% conversion.
Per SKU × per store × per day predictions. Weather, events, holidays modeled.
Automated re-order, warehouse-to-store distribution, stock rotation.
Per-customer recommendations, targeted promotions, lifecycle triggers.
Competitive pricing based on market, margin, elasticity. +1.5% margin lift.
500+ employees. Projects across multiple countries. Bid process took 2–3 weeks while competitors won projects in days. Cost overruns detected only after they'd blown budgets. We changed both.
2–3 weeks per bid. Competitors turned around in days and won projects.
Delays and overruns discovered after the fact, costing millions.
10,000+ documents per project. Retrieval took hours. Things got lost.
Manual audits, incidents handled after. Insurance costs climbing.
Trained on historical wins. Full estimate in 1–3 days. Win rate doubled.
Real-time progress vs baseline. ML flags risk 60–90 days ahead.
Semantic search across specs, contracts, RFIs. Seconds, not hours.
PPE compliance monitored live. Unsafe behavior auto-flagged.
400+ employees, €80M+ revenue, 15–20% annual churn eating €2M in lost customer lifetime value. 50k+ monthly support calls, 70% of them trivial.
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