Engineering and security that protects your margin.
eCommerce and D2C teams lose more to fraud, account-takeover, and downtime than to bad ads. We build the security, performance, and engineering capacity that protects your margin — without slowing the merch and growth teams.
- 01Account takeover, credential stuffing, gift-card fraud
- 02PCI-DSS scoping when you accept cards directly
- 03Bot mitigation that does not break legitimate buyers
- 04Catalog scale + checkout latency at peak (sale events, drops)
- 05AI for personalization, search, recommendations — without ML team
- PCI-DSS v4.0If you store, process, or transmit card data — even via a third party.
- DPDPA + GDPRCustomer data handling, consent for marketing, cross-border transfers.
- CCPA + state consumer lawsIf you sell to US customers — opt-out, data access, deletion rights.
- Consumer Protection Act (India)eCommerce rules; grievance redressal mechanism required.
Fraud + ATO defense
Detection rules + bot mitigation tuned for retail traffic patterns.
Explore →PCI scoping + VAPT
Reduce PCI scope (tokenize), then test the in-scope surface.
Explore →Performance + scale engineering
Checkout latency, catalog scale, peak-traffic readiness.
Explore →AI personalization
Search, recommendations, dynamic merchandising — production-grade.
Explore →AI agents for ops
Returns triage, customer-support copilots, vendor reconciliation agents.
Explore →Can you do peak-event readiness (sale days, product drops)?+
Yes. We do load modeling, autoscale tuning, queue + caching design, and a dry-run with synthetic traffic. We also build a war-room runbook for the day.
Do you handle bot mitigation without breaking legitimate buyers?+
We layer challenge-based (Turnstile/hCaptcha), behavioral (device fingerprinting), and rule-based (rate limits per pattern). Tuned to keep false-positives low on real buyers.
How do you do AI personalization without an ML team?+
We build with off-the-shelf foundations (vector search, hybrid retrieval, lightweight fine-tunes) so you do not need to hire ML scientists. The system is operable by your engineering team.