Security and AI for High-Volume Commerce
E-commerce platforms process millions of transactions daily and are prime targets for fraud, data breaches, and DDoS attacks. We provide comprehensive security testing, fraud prevention AI, and scalable cloud infrastructure.…
D2C platforms lose 1.5–3% of GMV to payment fraud. Peak sale events attract coordinated bot attacks and carding attacks that overwhelm manual review queues.
Flash sales create 8–15× normal traffic spikes within seconds. Under-provisioning causes outages; over-provisioning wastes 40–60% of cloud budget on idle capacity.
Processing payment card data creates PCI-DSS scope that touches 60–80% of the tech stack. Annual QSA assessments are costly and disruptive.
Specific capabilities we've built and run for E-commerce organisations — not PowerPoint features.
Real-time ML scoring of every checkout transaction detecting account takeover, card testing, and CNP fraud with <0.1% false-positive rate.
Behavioural fingerprinting distinguishing human shoppers from scrapers, credential-stuffing bots, and flash-sale scalpers.
Predictive auto-scaling and chaos engineering ensuring 99.95% uptime during Big Billion Day and festive flash sales.
AI inventory reconciliation, supplier risk scoring, and last-mile delivery anomaly detection reducing stockouts and fulfilment delays.
Consent management, data minimisation, and breach notification workflows aligned to India's DPDP Act and GDPR requirements.
Automated network segmentation validation, log retention, and quarterly ASV scan orchestration keeping you continuously PCI-DSS compliant.
D2C Fashion & Electronics Platform (₹3,200Cr GMV, 18M registered users)
₹6Cr in fraud losses during a single Diwali sale. Bot traffic consuming 35% of compute resources during peak hours. Manual payment review causing 12% checkout abandonment, eroding conversion.
Deployed AI WAF with ML fraud scoring integrated directly into the payment gateway API, a bot mitigation layer at the CDN edge, and predictive auto-scaling policies using 3 years of historical traffic patterns.
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