Aviato Consulting

Retail & E-Commerce Cloud Solutions

Modern cloud data, real-time inventory synchronization, BigQuery lakehouses, and agent-ready commerce architecture for retail enterprises.

Real-Time Commerce & AI Search

Real-Time Cloud & AI Architectures for Modern Retail

Modern shoppers demand unified inventory visibility across physical stores and digital channels, sub-minute order fulfillment, and personalized discovery. We engineer real-time streaming lakehouses and Gemini AI concierges on Google Cloud that drive customer loyalty and margin growth.

The 4 Pillars of Modern Retail Transformation

Moving from legacy overnight batch syncs to real-time event-driven commerce.

Real-Time Inventory Streaming

Eliminate ghost inventory and out-of-stock cancellations. We build real-time CDC data pipelines between POS registers, ERPs (SAP/Oracle), and e-commerce stores using Datastream and Pub/Sub.

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Omnichannel BigQuery Lakehouse

Consolidate physical store receipts, online browsing sessions, and loyalty programs into Google BigQuery to power instant basket-affinity analysis and personalized promotions.

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Agentic Customer Experience

Deploy autonomous conversational shopping concierges with Gemini Enterprise to handle real-time shipment inquiries, initiate returns, and verify local shelf stock 24/7.

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Vertex AI Search & Recommendations

Replace zero-result keyword searches with semantic neural search and intent-driven recommendation models that boost conversion rates and average order values.

Agentic shopping: your next big customer isn’t a person

Since February 2026 this has been the thing retailers are scrambling to build for. A growing share of shopping traffic is an AI agent acting for a customer. It reads your catalogue, compares you against four competitors, checks whether the size is actually in stock, and in a rising number of cases completes the purchase without the customer ever loading your product page.

That’s a channel shift, and channel shifts reward whoever is ready early.

Why this is an opportunity rather than a threat

The retailers who panic about agents are the ones whose advantage was friction. If your conversion depended on a shopper being too tired to check three other sites, an agent removes that. Nothing to be done there.

But most retailers lose sales for the opposite reason. A customer can’t tell whether the item is in the store down the road, the size chart is a JPEG, delivery timing appears only at checkout, and the returns policy is four clicks deep. Human shoppers give up quietly. An agent gives up instantly and tells the customer you had nothing suitable.

Fix the machine-readability and you win demand you were already losing. Clean structured data, accurate real-time stock, and honest delivery promises are exactly what an agent rewards, and they happen to be what human customers wanted anyway. Which is the point: this isn’t a separate agentic strategy bolted on, it’s the merchandising hygiene you’ve been deferring, now with a revenue number attached.

What an agent needs from you

Structured product data first. Schema.org product markup, a well-formed Merchant Center feed, and attributes that mean something (actual fabric composition, actual dimensions, actual fit) rather than marketing adjectives. An agent can’t infer that “generous cut” means size up.

Real-time inventory second, and this is where most estates fall over. If your stock position is a nightly batch, an agent will confidently promise a customer something you sold this morning. That failure costs more than a missed sale, because the customer blames you rather than the agent. Streaming inventory through Pub/Sub and Dataflow into a serving layer that answers in milliseconds is the fix, and it’s the same pipeline that makes click-and-collect trustworthy.

Then a programmatic surface. Agents interact through APIs and increasingly through Model Context Protocol servers that expose your catalogue, availability and pricing as callable tools. Emerging payment standards, including Google’s Agent Payments Protocol, aim to let an agent complete checkout with a verifiable mandate from the customer rather than a stored card. This part is still moving, and anyone who tells you the standards have settled is guessing. Building the data layer underneath is the no-regrets move, because every version of this future needs it.

The uncomfortable part

Agents comparison-shop without loyalty or fatigue. If your only differentiator is price, agentic traffic will compress your margin faster than any price-comparison site did. Retailers with genuine differentiation, exclusive range, reliable next-day delivery, decent returns, service that solves problems, do better in an agent-mediated market than in a search-mediated one, because agents can actually read and weigh those attributes. Retailers competing purely on being findable will struggle.

We’d rather say that plainly than sell you an agent strategy that can’t fix a positioning problem.

Fixed price, fixed date

Talk to an architect who has done this before.

Bring your current setup and the outcome you need. You will get a view on the approach, the risks and roughly what it costs.

Book a 20-min architecture call

Straight to a senior GCP architect. No SDR, no slide deck.

Not ready to talk? See how we migrated Hapana off AWS →

Or call +61 2 8359 9507 · Hello@aviato.consulting

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