Route return exceptions faster.
Classify reason codes, attach order history, check policy, and send high-value cases to a reviewer.
Google Cloud Premier Partner
Elastic Generative AI Partner
70+ certified engineers
Retail and commerce platforms
AI is changing retail. SquareShift helps turn it into working products, workflows, and platforms.
We work inside the systems retail runs on: product discovery, merchandising, supplier reporting, returns, store operations, and marketplaces — with AI, data, search, observability, and engineering practices built for peak trade.
01 Credibility in retail
We have run search, observability, and reporting on live retail systems during peak trade.
Product discovery, Elastic operations, BI, cloud data platforms, commerce engineering, and live log migration while the storefront kept trading.
Partner and delivery base
Delivered signals
- 2 weeks From discovery to a working Elastic App Search prototype for a web-to-print retailer.
- 50M visits Monthly e-commerce visits kept under unified observability for a legacy department store chain.
- 2.2B documents Migrated from Graylog to Elastic Cloud for a commerce agency running global fashion brands.
Enrich product data before launch.
Generate and validate attributes, descriptions, care notes, image tags, and marketplace-ready fields.
Bring supplier documents into systems.
Extract packs, price files, product specs, compliance forms, and onboarding data into governed workflows.
Support agents get the full case.
Summarize customer history, order status, delivery notes, return policy, and next action in one view.
Keep marketplace listings consistent.
Check titles, taxonomy, required fields, content rules, and channel-specific exceptions before publishing.
Move campaign requests into production.
Turn briefs, asset checks, offer rules, promo calendars, and approval steps into a tracked workflow.
See performance while plans can change.
Ask which categories, stores, channels, or campaigns are behind plan and see the governed driver view.
Buyers work from one margin number.
Answer assortment, margin, sell-through, stock cover, and markdown questions from approved definitions.
Demand and availability stay connected.
Compare demand signals, stock position, replenishment risk, transfers, and substitute products in one flow.
Marketing sees performance by offer.
Join spend, traffic, conversion, basket, margin, and return rate so campaign decisions use the same base.
Partners get controlled reporting.
Give suppliers and brand partners governed views of their sell-through, stock, returns, and promotion data.
Store leaders get operational answers.
Answer staffing, availability, returns, service, and local campaign questions from approved retail metrics.
Protect reports the business uses daily.
Catalogue the sales, inventory, margin, traffic, loyalty, finance, and operations dashboards before migration.
Settle definitions before cutover.
Align sell-through, gross margin, stock cover, returns, campaign attribution, and conversion logic.
Compare old and new side by side.
Run data, SQL, visual, and stakeholder checks so migration issues surface before the reporting switch.
Turn reporting into a product.
Embed Looker reporting in controlled portals for suppliers, marketplaces, franchisees, and brand partners.
Replace manual packs with governed BI.
Move weekly trading packs, store packs, and supplier reports into reusable governed reporting workflows.
Get buyers and planners onto the new layer.
Take buyers, planners, finance, marketers, and store teams through the reporting model they now work from.
Shoppers ask in real language.
Match occasion, size, fit, material, budget, and availability against the products you can sell.
Fix demand the site already missed.
Mine zero-result and weak-ranking queries, then tune relevance where shoppers already show intent.
Trading teams keep ranking control.
Give merchandisers boost, bury, promote, and seasonal controls inside the search operating model.
Answers cite your own sources.
Answer fit, care, compatibility, warranty, returns, and delivery questions from approved content.
Agents find product facts faster.
Search product docs, policies, order notes, substitutions, and troubleshooting content from one interface.
Normalize search across channels.
Use shared product meaning across storefront, marketplace, partner portal, and internal tools.
Watch the full commerce stack.
Unify web, app, search, payment, order, inventory, integration, and infrastructure signals.
Find drift before the incident.
Use anomaly detection on traffic, latency, errors, queues, search behavior, and data pipeline health.
Monitor discovery quality.
Track zero results, slow queries, ranking shifts, content gaps, answer quality, and failed conversions.
Move logging platforms safely.
Migrate from Graylog, Splunk, or self-managed Elastic while live storefronts keep generating data.
Right-size always-on platforms.
Cut over-provisioned clusters and keep enough capacity for campaign bursts and seasonal traffic.
Give teams one incident view.
Align eCommerce, store operations, service, infrastructure, and vendor teams around the same signal.
07 AI-led app and platform engineering
The commerce app, the supplier portal, the operations tool — built by a team that is already assembled.
Commerce applications, platform services, internal tools, data products, and automation, with senior engineers accountable for what ships.
Vanguard Teams
A focused team builds a proof of concept in a week, an MVP in a month, and production in three months for typical apps.
- Commerce portal and marketplace features
- Supplier reporting and product-data tools
- Returns, service, and operations apps
Embedded enablement
We work with your engineering team when they already use AI coding tools and need better delivery patterns, review, and operating discipline.
- AI-assisted delivery playbooks
- Architecture, testing, and review routines
- Patterns for production AI features
Forward Deployed Engineers
A senior engineer embeds with the business or operations team and ships working code against the real systems from day one.
- Merchandising and trading workflow builds
- Operations automation against live systems
- Short-cycle apps for immediate constraints
08 AI observability for technical buyers
Your engineers already use AI. So do your shopping assistants.
Compass AI covers the engineering teams using AI coding tools. Atlas AI covers the AI applications already running in front of customers.
Compass AI
Compass AI shows what AI coding tools cost, who uses them, where security risk appears, and whether adoption is real across engineering teams.
- Track AI coding spend by team, tool, model, and project.
- See secrets, customer data, and compliance risk in prompts.
- Measure adoption for retail engineering teams building commerce systems.
Atlas AI
Atlas AI observes AI applications already in production, including recommendations, shopping assistants, RAG answers, agent workflows, and AI search answers.
- Track AI application cost, security, prompt operations, and compliance.
- Use Prompt Workbench to manage prompts like production code.
- Measure answer quality for shopping, service, search, and internal assistant experiences.
Bring us the retail problem costing you margin, conversion, or hours. We will scope what can ship first.
Talk to SquareShift