Customer signals turned into measurable business outcomes across Banking, Telco, Healthcare, Insurance, Wealth, Government, Aviation and Life Sciences.
Deployed across enterprises with 10M–200M customers in
Based on production deployments across enterprises with 10M–200M customers in banking, telco, healthcare and regulated industries.
Replacing batch campaigns with a real-time decisioning system that acts on individual customer signals as they happen — and learns with every interaction.
Transactions, usage events, clinical signals — unified from any system in real time, without replacing existing infrastructure.
Propensity, churn risk, next best action — Allyvate AI segments and scores each individual customer continuously, in real time, with explainable reason codes.
Personalised engagement delivered across every channel — push, SMS, WhatsApp, email, agent prompt — automated or human-assisted, governed by Inform consent + audit at source.
Every outcome attributed in real time. Models improve with every decision. Performance dashboards available to every stakeholder.
Integrated with core banking systems. Compliant with RBI, SAMA, MAS and PDPL.
Cross-sell acceptance at salary credit event
A large private bank with 30M+ retail customers and over 70% digital channel adoption. Mobile banking is the primary product interaction and service touchpoint.
Cross-sell campaigns were batch-scheduled and disconnected from real-time customer moments. The salary credit event — the single highest-intent window for savings and investment products — was being missed entirely.
Sense connected the core banking event stream and mobile SDK. Decide modelled salary-receipt propensity using balance history and behavioural traits. Allyvate AI selected the Next Best Offer per customer in under 200ms. Act delivered a personalised push notification within 3 seconds of the event firing.
3.2× uplift in cross-sell acceptance. Time-to-market for new product offers reduced from 6 weeks to 3 days. The bank built an agile, event-driven commercial operating model around real-time customer moments.
Reduction in voluntary customer attrition
A leading bank operating in a highly competitive retail banking market with strict SAMA and PDPL regulatory requirements governing data use and customer communications.
Customer attrition was identified only through branch visits or call centre complaints — too late to intervene. No capability existed to detect exit intent early or trigger personalised retention journeys at scale.
Sense unified core banking, CRM and digital channel data. Decide built a churn propensity model using 45+ signals, flagging at-risk customers 45 days before predicted exit. Allyvate AI selected the retention action and channel per value tier. Inform provided full SAMA-compliant audit trails.
40% reduction in voluntary churn. Retention shifted to a real-time, signal-driven operating model — replacing manual campaign planning with continuous decisioning, under defined controls.
Improvement in loan application completion rate
A digital-first lending platform with predominantly mobile-originated loan applications. High drop-off rates at the document submission stage were limiting origination volumes.
Application abandonment was tracked at aggregate level only. No capability to detect in-session drop-off intent or intervene within the same session — recovery was a next-day batch exercise.
Sense captured session behaviour via mobile SDK and origination APIs. Decide identified real-time drop-off signals — inactivity, scroll behaviour and stage-specific exit traits. Allyvate AI selected the recovery nudge per stage. Act delivered an in-session intervention before the session closed.
28% improvement in loan application completion. Conversion recovery moved from a reactive batch model to a real-time, agentic digital origination capability — fundamentally changing acquisition unit economics.
CTR uplift on push notifications — with consent and compliance preserved
IDBI Bank, an Indian public-sector commercial bank, was operating in a regulated BFSI environment with high notification fatigue. Its mobile experiences span the GO Mobile+ banking app, IDBI eRupee CBDC application and segment-specific products such as the Senior Citizens Savings Scheme.
Batch-based pushes were driving low engagement and rising opt-outs. The bank needed to increase adoption of priority features without compromising customer trust or regulatory compliance — difficult to do in a category where most banks default to broadcast notifications.
Appice deployed real-time segmentation by lifecycle, intent and activity. Decide drove predictive timing and frequency capping; Allyvate AI personalised content and selected deep-linked CTAs per customer; Inform enforced consent-based delivery with full audit trails — PII never leaving the bank's perimeter.
+15% push open rates and +41% CTR uplift. +18% adoption of security and priority features. +12% improvement in 30-day retention. Opt-outs reduced 5% through lower notification fatigue. Push became a measurable, compliance-safe growth channel rather than a liability.
Faster time-to-market for new journeys, offers and experiments
Gulf International Bank is a pan-regional financial institution headquartered in Bahrain, with a heritage in wholesale banking, treasury and capital markets across the GCC. As part of its strategic evolution into digital retail and SME banking, GIB launched modern mobile and online applications — and customer expectations shifted with them.
Personalisation was rules- and segment-based; channels operated independently; marketing innovation depended on long IT change cycles; Saudi regulatory and security requirements constrained experimentation. Moving beyond campaigns required architecture, not features.
Sense assembled a unified, live customer state. Decide delivered intent detection, propensity scoring, churn risk and next-best-action selection from a governed ML Studio. Allyvate AI ran closed-loop learning with human-in-the-loop oversight. Inform enforced centralised consent and preference management aligned to SAMA.
~30–35% increase in digital engagement; ~20–25% uplift in conversion vs batch campaigns; ~15–20% increase in priority-feature adoption. Operationally: 35% reduction in message fatigue, 4× faster time-to-market for journeys, reduced IT dependency. Governance: 100% auditable and explainable customer decisions, SAMA-aligned.
Cross-sell at the salary-credit moment — real-time, RBI-aligned
Bank of India is one of India's largest public-sector banks, serving a vast retail base across metro, semi-urban and rural branches alongside the BOI Mobile / omni-neo digital channel.
Engagement ran on batch campaigns and calendar schedules. High-intent moments — a salary credit, a balance threshold, an idle account — passed before any action was taken.
Sense unified core-banking, app and branch signals. Decide scored eligibility and propensity at the salary-credit event. Allyvate AI personalised; Inform enforced RBI-aligned consent and audit.
Real-time next-best-action at salary credit lifted cross-sell acceptance ~3×; digital engagement rose ~28%; dormancy fell ~24%. Illustrative — pending bank approval.
Integrated with BSS/OSS event streams. No infrastructure replacement required.
Reduction in voluntary subscriber churn
A national mobile operator with 15M+ subscribers in a saturated market facing aggressive tariff competition from new entrants and MVNOs.
Voluntary churn was detected only at the port request stage — after the subscriber's decision was made. Retention spend was wasted on low-risk subscribers and arrived too late for high-risk ones.
Sense connected BSS, CRM and real-time network event feeds. Decide modelled churn propensity using dropped call rate, data frustration signals and usage decline trends. Allyvate AI selected retention offer value and timing per LTV tier. Act delivered personalised interventions across SMS, push and call centre agent prompts.
35% reduction in voluntary churn. Retention shifted from a reactive campaign function to a proactive, AI-driven commercial capability — a decisive change in the operating model from reactive to predictive.
Higher plan upgrade conversion vs batch campaign
A Tier-1 mobile operator with over 200M subscribers and intense competition for data revenue in the mid-market segment. High smartphone penetration but stagnating ARPU growth.
Plan upgrade campaigns were batch-scheduled against static segments. Revenue opportunities at peak intent moments — when subscribers hit data limits mid-session — were systematically missed.
Sense captured real-time OSS usage events at 85% data threshold. Decide modelled price sensitivity and upgrade propensity. Allyvate AI selected the optimal plan and offer construct. Act delivered the contextual upgrade offer in-app within 2 seconds of trigger. Learn continuously improved the model.
2.8× higher plan upgrade conversion. ARPU uplift delivered at scale through an agentic, event-driven upsell engine — operating 24/7 without manual campaign intervention.
Reduction in inbound complaint volume
A regional mobile operator serving prepaid-dominant subscribers across multiple markets. Contact centre capacity was significantly constrained relative to subscriber base size.
Network outages triggered a flood of inbound complaint calls that overwhelmed support operations. Service failures were managed reactively with no proactive outreach capability — damaging NPS and subscriber trust.
Sense connected OSS network event feeds and subscriber master database. Decide identified affected cohorts segmented by network exposure and LTV tier. Inform orchestrated high-volume personalised proactive outreach across SMS and in-app within minutes of detection — before affected subscribers could initiate contact.
60% reduction in inbound complaint volume. Proactive, agentic service recovery transformed both the customer experience model and contact centre cost structure — turning a reactive problem into a differentiating capability.
Integrated with EMR/EHR systems. Consent-first, HIPAA-ready.
Improvement in outpatient appointment show rate
A large hospital network with 20+ locations and over 2M outpatient appointments annually. Patient engagement delivered almost entirely through generic bulk SMS reminders at fixed intervals.
Appointment no-show rates were consistently high. Reminder communications were one-size-fits-all with no differentiation by patient risk profile, appointment type, clinical priority or preferred channel.
Sense connected the EMR system and consent management layer. Decide modelled no-show risk using adherence history, appointment type and demographic traits. Allyvate AI selected reminder type, channel and send time per patient. Act delivered personalised reminders via WhatsApp, SMS and voice for highest-risk patients.
28% improvement in appointment show rates. Clinical capacity utilisation increased across the network. A data-driven, patient-centric engagement model replaced broadcast reminders — building a measurably more agile care operations capability.
Increase in medication adherence — chronic disease
A pharmaceutical patient support programme covering chronic disease patients across diabetes, hypertension and respiratory conditions, delivered through a branded patient app.
Medication lapse rates were high and correlated directly with poor clinical outcomes and programme attrition. Reminders were generic and not calibrated to individual adherence histories, lapse signals or condition severity.
Sense connected the patient app, pharmacy refill data and EMR event stream. Decide modelled lapse propensity using refill cycle signals and missed dose patterns. Act delivered personalised adherence nudges at the predicted lapse moment. Allyvate AI adapted message tone, channel and escalation path per engagement history.
45% increase in medication adherence. Programme re-enrolment rates increased. Clinical outcomes improved measurably — demonstrating a shift toward a proactive, digital-first patient engagement model with genuine health impact.
Reduction in 30-day hospital readmission rate
A health insurer managing post-acute care coordination for hospitalised members. Regional regulations require documented post-discharge engagement within 30 days of discharge.
Post-discharge follow-up was manual, inconsistent and coordinator-dependent. High readmission risk patients were not systematically identified or reached within the critical recovery window — leading to preventable readmissions and excess claims costs.
Sense connected hospital EMR discharge events and the insurer member database. Decide modelled readmission risk using condition type, procedure and social determinant traits. Allyvate AI designed personalised follow-up sequences per risk tier. Act delivered automated check-ins via WhatsApp and SMS with care coordinator escalation for highest-risk members.
22% reduction in 30-day readmission rate. Post-discharge coordination shifted to a real-time, signal-driven operating model — systematic, personalised and scalable — reducing avoidable claims costs.
Connected to policy management and claims systems. Compliant with IRDAI, SAMA and CBUAE requirements.
Improvement in policy renewal conversion rate
A large life insurance provider with millions of policies reaching annual renewal. Renewal outreach relied on centralised batch communications with no personalisation by risk profile, policy value or life stage.
Lapse rates spiked in the 30-day renewal window due to generic, poorly-timed communications. High-value at-risk policyholders received the same message as low-risk renewals — and attrited silently.
Sense connected the policy management system and digital behavioural data. Decide modelled lapse propensity using payment history, engagement recency, sum assured and life-stage signals. Allyvate AI designed personalised renewal journeys per risk tier with automated agent escalation. Act executed multi-channel outreach across push, WhatsApp and agent prompts.
2.5× improvement in renewal conversion. Policy lapse reduced by 28%. Renewal transformed from batch outreach into a proactive, AI-driven lifecycle retention capability with a measurable shift toward a data-driven commercial operating model.
Cross-sell conversion from post-claim moments
A general insurer offering motor, home and life products. Post-claim engagement was limited to settlement notifications — high-trust, high-engagement moments not being leveraged for relationship deepening.
Claim settlement moments — when customer trust and attention are at peak — generated no onward commercial engagement. Revenue and retention opportunities were consistently unrealised at the most impactful lifecycle point.
Sense captured claim settlement events and policy data. Decide modelled cross-sell propensity using product gap signals and claim type traits. Allyvate AI evaluated compliance eligibility before surfacing any offer. Act delivered consent-compliant outreach within 24 hours of settlement across WhatsApp and push.
38% increase in post-claim product engagement. 1.8× cross-sell conversion from claim moments. The team moved from a reactive claims model to an agentic, event-driven relationship model — embedding commercial capability into claims resolution.
More insurance case studies available under NDA.
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Connected to portfolio management platforms and market data feeds.
Increase in proactive RM-initiated client conversations
A wealth management business embedded within a large regional bank, serving HNI and affluent customers. Relationship Managers averaged 200+ clients per portfolio with outreach driven by quarterly review cycles.
Advisory triggers — portfolio concentration breaches, rebalancing opportunities, life-stage events and market movements — were missed because RMs relied on manual scanning. Client engagement was reactive rather than proactive.
Sense connected core banking, portfolio management and market data feeds. Decide modelled advisory trigger signals — concentration risk, rebalancing need and life-stage events per client. Allyvate AI orchestrated real-time RM task alerts per trigger type. Learn attributed RM-client interactions to portfolio outcomes.
3× increase in proactive RM-initiated conversations. Cross-sell and upsell conversion improved by 40%. RMs shifted from order-takers to proactive advisors — a cultural transformation driven by an agentic advisory operating model.
Improvement in HNI client digital engagement rate
A private bank serving HNI clients across multiple Southeast Asian markets. Digital adoption was accelerating but the advisory interaction model had not evolved beyond email and in-branch meetings.
Personalised advisory communications were resource-intensive and inconsistently delivered. High-value clients were receiving generic market updates identical to the mass-affluent segment — eroding perceived private banking value.
Sense connected portfolio data, interaction history and market intelligence feeds. Decide built client engagement propensity models using product holding gaps and life-stage signals. Allyvate AI generated personalised, compliance-vetted insight summaries per client. Act delivered hyper-personalised communications via private banking app and WhatsApp at the moment of relevance.
40% improvement in HNI client digital engagement. Client satisfaction scores improved materially. The bank established a scalable, agentic personalisation capability that would previously have required a tenfold increase in RM headcount.
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Connected to national identity and service platforms. Fully compliant with data residency and citizen data regulations.
Improvement in digital service completion rate
A government services authority administering digital public services to millions of citizens and residents. Service uptake was below target despite high digital channel penetration and a well-funded digital transformation programme.
Licence renewals, permit applications and benefit entitlements were communicated through broadcast notifications that generated low completion rates and high inbound call centre load. Citizens were not reached at the right moment with the right service prompt.
Sense connected citizen identity and entitlement databases with digital service platforms. Decide modelled service eligibility urgency and completion propensity using expiry timelines and service history traits. Inform orchestrated high-volume personalised outreach at scale across SMS, app and portal. Learn tracked completion funnels per communication type in real time.
2× improvement in digital service completion. Inbound call volume for renewal reminders reduced by 35%. The authority shifted from broadcast public communications to a proactive, personalised citizen engagement model — advancing its digital transformation mandate.
Reduction in vaccination programme drop-off rate
A national public health agency running a multi-dose vaccination programme across urban and rural populations. Completion rates for multi-dose schedules were significantly below clinical targets.
Citizens receiving a first dose were not reliably completing follow-on doses. Reminders were broadcast and undifferentiated — no capability to predict dropout risk or personalise follow-up by vaccination history, location or communication preferences.
Sense connected the national immunisation registry with mobile and SMS infrastructure. Decide modelled dropout propensity using dose completion history, geolocation and demographic traits. Allyvate AI selected reminder timing, channel and message variant per citizen. Inform orchestrated personalised dose reminders at scale with community health worker escalation for highest-risk cohorts.
35% reduction in multi-dose drop-off. Programme completion reached clinical targets for the first time. A data-driven, agentic public health engagement model was established — scalable across disease programmes and replicable to other preventive health campaigns.
More public sector case studies available under NDA.
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Connected to PSS, DCS, loyalty and OPS systems. Compliant with IATA, EU 261, DOT and DGCA passenger-rights frameworks.
Reduction in passenger no-show after disruption
A national flag carrier operating across MENA, South Asia and Europe with 200M+ annual passenger interactions. Operational disruptions (weather, ATC, technical) generated hundreds of thousands of impacted passenger journeys annually.
Disruption notifications were broadcast, generic, and frequently arrived after passengers had already taken matters into their own hands. Self-service rebooking adoption was below 30%; the rest defaulted to call centres or no-shows — with high cost and downstream connection failures.
Sense connected PSS, OPS, loyalty and customer service into one real-time signal stream. Decide ranked rebooking options per passenger using fare class, status, schedule flexibility and downstream connections. Act fired multi-channel (push, WhatsApp, SMS, voice) with consent-aware fallback at the moment of disruption. Learn measured rebooking completion and no-show recovery in real time.
40% reduction in disruption-related no-shows. Self-service rebooking adoption rose to 68%. Call-centre disruption volume reduced 45%. Downstream connection misses cut significantly.
Lift in ancillary attach rate
A fast-growing LCC carrying 30M+ passengers annually. Ancillary revenue (bags, seats, meals, priority) was a strategic growth lever — but attach rates lagged peer benchmarks.
Bag, seat and meal upsells were sent in pre-flight email batches with low engagement. The actual moment of decision — at online check-in and kiosk — was being missed entirely. No mechanism existed to personalise the offer per passenger or per route.
Sense connected DCS, loyalty and PSS for real-time passenger context. Decide modelled attach propensity per passenger per ancillary using past purchases, route and time-to-flight. Allyvate AI generated personalised offer copy and ranked offers. Act fired at the check-in moment via app, kiosk and email. Learn closed the loop on attach rate per ancillary type.
3.2× lift in ancillary attach rate. Average ancillary revenue per passenger up 28%. Margin contribution from ancillaries became a material driver of route-level profitability.
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Connected to Veeva CRM, medical-events platforms and patient support programmes. Compliant with HIPAA, MHRA, FDA, EMA and pharma promotional codes.
Lift in HCP engagement rate
A global pharmaceutical company with 5,000+ field reps engaging 80K+ healthcare professionals across 40+ markets. Field-force productivity was under pressure as HCPs became harder to reach and email open rates declined.
HCP communications were broadcast, timed to internal product launch cycles rather than HCP signals. The rep workflow couldn’t react to live events — a conference visit, a prescription pattern change, a regulator announcement — that should trigger personalised, compliant outreach.
Sense connected Veeva CRM, medical-events platforms, prescription data and content engagement systems. Decide modelled HCP engagement propensity per content type using prescription history and behavioural signals. Allyvate AI generated compliance-checked personalised content. Act orchestrated rep notifications and direct HCP outreach across approved channels. Learn measured engagement and prescription-correlation lift.
28% lift in HCP engagement (opens, content consumed, rep meetings booked). Field-force productivity up 18%. Compliance approval cycle on content reduced from weeks to days through pre-approved templates and automated checks.
Improvement in patient adherence on specialty regimens
A specialty pharma operating in immunology and oncology. Patient adherence on multi-step specialty therapies was a critical clinical and commercial KPI — dropout cost was high in both outcomes and revenue.
Adherence support was uniform across patient cohorts — broadcast reminders, generic helplines. Patients at high dropout risk weren’t identified early; those who dropped off were detected only after the fact, when intervention was too late.
Sense connected patient support program data, refill data, side-effect reports and patient-reported outcomes. Decide modelled dropout risk per patient per regimen stage. Allyvate AI generated personalised adherence content per patient and therapy stage. Inform delivered via app, SMS and patient-support team handoff for highest-risk cohorts. Learn tracked adherence rates and outcome correlation.
30% improvement in patient adherence on specialty regimens. Patient-support team capacity freed by 25% as low-risk patients self-served. Outcome data shows better long-term retention on therapy and clinically meaningful improvement in completion rates.
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