AI · Cloud · Staffing for Retail & E-commerce
We connect every sales channel, personalize the shopping experience and optimize the last mile.
Los 3 retos tech de Retail y E-commerce
Omnichannel experience the customer actually feels
Unified inventory, shared purchase history between store and web, click-and-collect that works Saturday at 6pm. Not a slogan — it's a data and orchestration problem.
Urban last mile in 2 hours
The best routers fail if stock per store is outdated or if delivery promises ignore actual logistics cutoff times. Demand inventory streaming and continuous simulation.
Personalization that doesn't violate purchase intent
Recommending what they already bought kills conversion. Recommending without regional stock context frustrates. The recommender must know catalog, inventory, and customer moment.
Checkout that doesn't lose carts at the final step
Each additional regional payment method (PSE, Nequi, Pix, OXXO) increases conversion but adds technical friction. Integration must not degrade Core Web Vitals or bloat the bundle.
Low-margin operation that lives on data
Retail operates on 3–8% margins. Every point of inefficiency in cloud, logistics, or advertising eats into profit. A unified data warehouse is no longer optional.
Cómo el marco I+C+S resuelve esto
AI for Retail
Recommendation engines, demand prediction, dynamic pricing and chatbots with generative AI.
Cloud for Retail
Elastic architectures for sales peaks, CDN for catalogs and microservices.
Staffing for Retail
Developers with experience in e-commerce platforms and ERP/POS integrations.
Industry challenges
Omnichannel experience the customer actually feels
Unified inventory, shared purchase history between store and web, click-and-collect that works Saturday at 6pm. Not a slogan — it's a data and orchestration problem.
73% of customers expect a consistent experience across channels (McKinsey).
Urban last mile in 2 hours
The best routers fail if stock per store is outdated or if delivery promises ignore actual logistics cutoff times. Demand inventory streaming and continuous simulation.
Personalization that doesn't violate purchase intent
Recommending what they already bought kills conversion. Recommending without regional stock context frustrates. The recommender must know catalog, inventory, and customer moment.
Checkout that doesn't lose carts at the final step
Each additional regional payment method (PSE, Nequi, Pix, OXXO) increases conversion but adds technical friction. Integration must not degrade Core Web Vitals or bloat the bundle.
69.8% of carts are abandoned at checkout, mostly due to friction.
Low-margin operation that lives on data
Retail operates on 3–8% margins. Every point of inefficiency in cloud, logistics, or advertising eats into profit. A unified data warehouse is no longer optional.
Regulatory frameworks we operate under
Payment Card Industry Data Security Standard
Applicable if you process payments on-site; avoidable with PSP redirect/iframes.
Law 1480 Colombia
Right of withdrawal, clear return policy, non-deceptive advertising.
Customer data processing
Marketing consent, right to erasure, accountable to SIC.
DIAN (Colombia), SAT (Mexico), AFIP (Argentina)
Issuance, validation, and storage per local regulations.
How we implement in this industry
Real patterns we have delivered, not theoretical slides.
Headless e-commerce with 1M+ SKU catalog
Next.js frontend with SSG + ISR, catalog served from ElasticSearch, CDN-optimized images, checkout with regional payment methods (PSE, Nequi, Pix, OXXO, credit card).
Outcome: 35% increase in conversion and Core Web Vitals in the green on 95% of URLs.
OMS Orchestrator with Unified Inventory
A real endpoint for stock across stores, warehouses, and dark stores. Distributed reservations with compensation, delivery promise simulation before confirming purchase.
Outcome: 40% reduction in cancellations due to out-of-stock.
Contextual recommender (customer + inventory + seasonality)
Catalog embeddings on pgvector, ranking that considers regional inventory and purchase recency. Ongoing A/B test against editorial baseline.
Outcome: AOV (average order value) +18% in tested segments.
AI Agent for post-sales support
Responds to order status inquiries, manages returns, executes scoped refunds with handoff to human agent. Integrated with ERP, carrier, and PSP.
Outcome: 68% first-contact resolution, 50% reduction in escalated tickets.
Our playbook for this industry
A repeatable method refined across 13 years and 7 countries.
Channel mapping, inventory and leak points
We identify where money is lost: checkout, outdated inventory, logistics, customer service. We prioritize by measurable impact on margin.
Headless + event-driven architecture
Decoupled frontend, catalog and inventory as single source of truth, asynchronous messaging for OMS, WMS and ERP.
Go-live by channel with exhaustive monitoring
First web, then mobile, then store. Each channel enters with conversion dashboards and error rates visible to the business.
Continuous optimization with FinOps + AB testing
Monthly cost-per-transaction review, experimentation based on business hypotheses, not UX intuition.
Industry signals you should know
Common tech stack
Questions from companies in this sector
All four. We choose based on volume, catalog complexity, and customization depth. For catalogs under 50K SKUs with few custom flows, SaaS platforms. For retail with proprietary OMS and multi-country operations, custom headless on Next.js + ElasticSearch.
Yes. We integrate with the dominant gateways in each market (PayU, ePayco, Wompi, EBANX, MercadoPago, Stripe). We validate conversion by method and optimize the presentation order at checkout.
Pre-warm infrastructure 2 weeks ahead, circuit breakers between critical services, virtual queueing if load exceeds threshold, dashboards with drilldown by country and channel. We monitor live with the client during the event.
Yes. We use middleware or direct REST/SOAP integrations depending on the ERP. The pattern is always an anti-corruption layer to prevent coupling the frontend to the ERP's release cadence.
First operational version in 3–4 months. Includes catalog, checkout, PSP integration, and base OMS. The following 2 months are dedicated to conversion fine-tuning and onboarding the second country.
Can your e-commerce handle the next Hot Sale without crashing?
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