SCNET · Enterprise IT · Ankara, Türkiye

Sanal Çekirdek

Keep inventory, order and customer context consistent across every channel.

Retail and ecommerce technology services cover systems where experience depends on inventory accuracy, pricing, orders, payments, fulfillment, and support as much as the interface. Sanal Çekirdek treats demand peaks and store connectivity as direct inputs to infrastructure and resilience design.

Omnichannel data and transaction flow

Ownership and freshness rules are defined for product, price, promotion, inventory, customer and order data. Stores, web, mobile, marketplaces and contact centers share transaction context.

  • Systems of record for product, price and stock
  • Order and fulfillment orchestration
  • CRM, ERP and marketplace integration
  • Error queues and reconciliation

Peak capacity and resilience

Campaign and seasonal demand is tested across databases, search, cache, payments, integrations, queues and support—not only the web tier. We observe the real transaction path and validate recovery.

  • Load and resilience testing
  • Autoscaling and capacity
  • Payment and third-party dependencies
  • DR and cyber recovery

Managed store, edge and network services

POS, electronic labels, cameras, sensors and store applications are managed through secure network zones and central visibility. The minimum service level that must keep running during connectivity loss is explicitly designed.

  • SD-WAN and link resilience
  • Store Wi-Fi and segmentation
  • Edge-device lifecycle
  • Running locally and synchronizing data

AI-assisted commerce and service

AI can support product discovery, customer service, demand forecasting and operational exceptions. Recommendations are constrained by consent, data quality, actual inventory and commercial rules, with human handoff for customer-impacting actions.

  • Grounded product-information assistant
  • Demand and inventory forecasting
  • Customer-service routing
  • Pricing and promotion decision support

How we work

  1. Bring channels and stock/price ownership into one table
  2. Derive the peak-season scenario from past campaign data
  3. Design order orchestration and the store network
  4. Pilot on one channel and a limited set of stores
  5. Roll out in stages against the campaign calendar

How success is measured

  • Order success, abandonment and error rate
  • Inventory and price consistency
  • Peak latency and capacity
  • First-contact resolution and AI handoff

Frequently asked questions

How are marketplace integrations managed?

Product, price, inventory, order, cancellation and return flows are treated as separate contracts. Rate limits, retries, error queues and reconciliation are essential for reliability.

Can stores continue during an internet outage?

That depends on local operating capability in POS and store applications. The minimum transaction set, local data, payment conditions and post-outage synchronization must be designed.

What data should AI recommendations use?

Customer signals that align with purpose and consent should be combined with current product, price and inventory data. Sensitive inference and manipulative patterns should be avoided, with impact measured.

What should be tested before peak periods?

Real customer journeys should be tested with payment and third-party dependencies under load, failure, slowdown and partial-outage scenarios. Homepage traffic alone is not enough.

Test the customer journey against the real dependencies in inventory and transaction flows.

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