Retail runs on real-time decisions — what to show a shopper, whether an item is in stock, how to price it, how to fulfill it — at traffic that swings from quiet to peak in minutes. The Akka Agentic AI Platform lets retailers build and run AI agents that act on live customer, catalog, and inventory data.
A shopper won't wait. Personalization, inventory, pricing, and fulfillment decisions have to land in milliseconds, against catalogs of hundreds of thousands of items, through demand that spikes on promotions and holidays. The systems behind them have to scale to the moment and keep the cost per session down.
Match shoppers to products, prices, and content on live signals — no pre-computed batch results.
Scales with promotional and seasonal demand and back down, so capacity follows traffic.
Serve thousands of predictions per second per model with batching and feature reuse built in.
Serve more requests on the same footprint, cutting compute cost per prediction and per order.
Retail runs AI directly against consumers — recommendations, pricing, and profiling that regulators increasingly govern for transparency and fairness. Akka tracks 189 AI regulations worldwide, mapped to enforceable controls and monitored as they change.
The same platform that runs retail through peak keeps the agents on it safe and accountable — a real-time check on every action, and a record that holds up.
Runtime filters catch prohibited or unsafe content before an agent can act on it.
Personal and confidential data is automatically removed from what agents read and write.
Every agent action is checked inline as it happens — pass, block, or flag — so an unsafe action never executes.
High-stakes actions escalate to a person for approval, and halt switches let a human stop an agent instantly.
Scenario, replay, stress, and adversarial red-team tests gate every change before production.
Every decision is written to a tamper-evident, hash-chained log, retained for years with legal hold.
Real-time, per-shopper recommendations across the full catalog.
Accurate, live stock and availability across channels and stores.
Route, batch, and fulfill orders reliably under peak load and strict SLAs.
Price and promote in real time against demand, inventory, and competition.
Forecast demand at SKU and store granularity to plan inventory and staffing.
Resolve orders and returns and contain fraud in real time on live account state.
Walmart rebuilt its web and mobile stack on Akka, moved ~40% of compute to commodity servers, cut page-load times 36%, and lowered long-term web infrastructure cost by up to 50%.
Read the story →Swiggy built its Data Science Platform on Akka, halved compute per prediction with micro-batching and feature reuse, and now scores every order-and-rider pairing inside a strict one-minute SLA.
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