AI for Retail & E-commerce. From Demand to Fulfillment
Agentic AI for merchandising, operations, and customer experience at the pace retail moves.
The opportunity
Retail and e-commerce run on thin margins and fast cycles. Merchandising, pricing, supply chain, and customer operations each carry a heavy decisioning load, and the teams running them can't wait for a BI report or a manual escalation. The last generation of forecasting made that worse: it was confident and wrong, and a model that looked flawless in backtest fell apart on the first promotion. Fintechy builds agentic AI that carries that decision load across forecasting, pricing, service, and fulfillment, and is honest about its own uncertainty.
Written for the CFO
The person who can stop a retail AI deployment has usually already paid for a forecast that missed. We design for them first. Every forecast ships with error bands and a stated confidence, not a single number pretending to be certain. The model shows its reasoning, so a merchant can check it rather than trust it blindly. A human owns the call on high-stakes pricing and inventory. And there is a defined fallback for when the model is wrong, because sometimes it will be.
Use cases we build
Demand forecasting
Forecasts demand and inventory with reasoning about promotions and events, and ships error bands with every number.
Merchandising copilots
Assortment, pricing, and markdown recommendations grounded in sell-through and margin, surfaced for a merchant to approve.
Customer service agents
Handle order inquiries, returns, and escalations in your brand voice, with handoff to a human on anything sensitive.
Fulfillment orchestration
Routing, exception handling, and carrier selection across fulfillment networks.
Content and catalog
Product content, attribution, and catalog enrichment across thousands of SKUs.
Marketing operations
Campaign copy, segmentation, and performance analysis grounded in your data.
Integration reality
We integrate with Shopify, Salesforce Commerce Cloud, SAP, NetSuite, and Oracle, alongside your OMS and CRM, on AWS, GCP, or Azure. We build against the systems your operation actually runs, not a reference configuration.
How we deliver
Diagnose
Map the workflows, the data landscape, and the decisions worth compressing, and find where AI has real leverage.
Architect
Design for your operational reality: error bands, human review, and brand guardrails built in from the start.
Build
Ship production-grade systems that surface their own confidence on day one.
Scale
Run, monitor, and govern the systems across the retail stack.
Forecasts arrive with error bands a merchant can trust or challenge, instead of a single number nobody believes. Customer service handles the routine contacts and escalates the rest. Merchants spend their time on judgment calls rather than pulling reports. Specific results are shared under NDA with an engagement owner who will stand behind them.
FAQ
No. It carries the decisioning load and surfaces recommendations with the reasoning attached, but the merchant keeps the call, and every forecast comes with error bands.
It absorbs the volume of routine decisions and contacts during peaks, escalating the exceptions to your team.
Yes, along with your OMS, CRM, and the surrounding operational systems.
A personalization engine ranks and recommends. Agentic AI reasons across the workflow and acts on it, with a human in the loop on high-stakes decisions.
Let's design your retail AI program
A working session tailored to your stack, your margins, and your priorities.