Industries / Retail & E-Commerce
Demand forecasts still come from spreadsheet trend lines, POS and CRM data live in separate systems, and support teams field the same questions hundreds of times a day. We build forecasting, data and AI for retailers who need real-time answers.
Inaccurate demand forecasting and fragmented POS/CRM data.
Demand forecasting models, a unified data pipeline across POS and CRM systems, and an AI customer chatbot.
Fewer stockouts, lower support cost, and real-time decisions.
How We'd Approach This
SKU-level demand forecasting built on your historical sales and seasonality data.
Pipelines that unify POS, CRM and inventory data into one source of truth.
A customer-facing chatbot for order status, returns and product questions.
How We'd Work Together
A free 30-minute conversation about your current process and where the gaps actually are.
A paid, structured review of your technology, data and process maturity — output is a scoped, prioritized roadmap.
Kickoff, technical discovery, then delivery sprints with regular check-ins — fixed-scope, T&M, or retainer.
Transition to managed services or a staff-augmentation retainer if you need ongoing capacity, not just a handoff.
Illustrative Engagement
A multi-location retailer was forecasting demand with spreadsheet trend lines, leading to recurring stockouts on fast-moving SKUs and excess inventory on slow ones.
Approach: A SKU-level demand forecasting model built on historical sales and seasonality data, integrated into existing inventory workflows.
Outcome pattern: Fewer stockouts and lower inventory carrying costs.
A Note on Reliability
Retail systems can't go down during a sale. Our cloud and DevOps foundation — 15 years of infrastructure delivery — means new AI and data systems get built on infrastructure already proven to handle real transaction volume, not a fragile prototype.