The productivity platform for measurable results
The productivity platform for measurable results
The productivity platform for measurable results
Retail Insight connects operations, leadership, and team culture to concrete decisions: the right staffing, at the right time, with documented impact.
Retail Insight connects operations, leadership, and team culture to concrete decisions: the right staffing, at the right time, with documented impact.
Retail Insight connects operations, leadership, and team culture to concrete decisions: the right staffing, at the right time, with documented impact.
Pilot: 90 days, 3–6 stores, weekly forecasts, and a clear baseline
Pilot: 90 days, 3–6 stores, weekly forecasts, and a clear baseline
Pilot: 90 days, 3–6 stores, weekly forecasts, and a clear baseline
Forecast customer flow before it reaches the store
Forecast customer flow before it reaches the store
Forecast customer flow before it reaches the store
The model combines historical footfall, sales, seasonality, and weather to forecast demand up to 8 weeks ahead.
The model combines historical footfall, sales, seasonality, and weather to forecast demand up to 8 weeks ahead.
The model combines historical footfall, sales, seasonality, and weather to forecast demand up to 8 weeks ahead.
Move hours to where demand actually appears
Move hours to where demand actually appears
Move hours to where demand actually appears
Traffic can vary sharply throughout the day while staffing stays flat. RIAS shows where hours create the most value.
Traffic can vary sharply throughout the day while staffing stays flat. RIAS shows where hours create the most value.
Traffic can vary sharply throughout the day while staffing stays flat. RIAS shows where hours create the most value.
Document impact, not just activity
Document impact, not just activity
Document impact, not just activity
Track visits per hour, sales per hour, and planned versus actual staffing so pilots and scaling can be defended with numbers.
Track visits per hour, sales per hour, and planned versus actual staffing so pilots and scaling can be defended with numbers.
Track visits per hour, sales per hour, and planned versus actual staffing so pilots and scaling can be defended with numbers.
A measurable pilot with a clear baseline
A low-risk test that shows whether smarter hours deliver better results
A low-risk test that shows whether smarter hours deliver better results
A low-risk test that shows whether smarter hours deliver better results
The pilot uses existing data and today’s planning tools. The goal is not necessarily fewer hours, but better placement of the hours you already have.
The pilot uses existing data and today’s planning tools. The goal is not necessarily fewer hours, but better placement of the hours you already have.
The pilot uses existing data and today’s planning tools. The goal is not necessarily fewer hours, but better placement of the hours you already have.
90 days
90 days
90 days
Month 1 is used for data collection and modeling. Months 2–3 are used for operation, follow-up, and learning.
Month 1 is used for data collection and modeling. Months 2–3 are used for operation, follow-up, and learning.
3–6 stores
3–6 stores
3–6 stores
Select small, mid-sized, and large stores. Compare against baseline and control stores before any wider rollout.
Select small, mid-sized, and large stores. Compare against baseline and control stores before any wider rollout.
Weekly delivery
Weekly delivery
Weekly delivery
Forecasts and resource recommendations can be used directly in today’s planning flow, without heavy integrations.
Forecasts and resource recommendations can be used directly in today’s planning flow, without heavy integrations.
Baseline first
Baseline first
Baseline first
Results are measured against an agreed baseline and comparable control stores, not against assumptions.
Results are measured against an agreed baseline and comparable control stores, not against assumptions.
Results are measured against an agreed baseline and comparable control stores, not against assumptions.
Human in control
Human in control
Human in control
Store managers keep the final say. Forecasts and recommendations support planning decisions; they do not replace them.
Store managers keep the final say. Forecasts and recommendations support planning decisions; they do not replace them.
Store managers keep the final say. Forecasts and recommendations support planning decisions; they do not replace them.
Choose the model that fits your business
A commercial model aligned with results
Combine a predictable platform fee with a performance-based component linked to documented operational improvement. The final model, baseline, and annual cap are agreed before launch.
A commercial model aligned with results
Combine a predictable platform fee with a performance-based component linked to documented operational improvement. The final model, baseline, and annual cap are agreed before launch.
A commercial model aligned with results
Combine a predictable platform fee with a performance-based component linked to documented operational improvement. The final model, baseline, and annual cap are agreed before launch.
EU AI Act
RIAS should be the safe choice for AI-assisted staffing in Europe
RIAS should be the safe choice for AI-assisted staffing in Europe
RIAS should be the safe choice for AI-assisted staffing in Europe
Prediction can influence working hours, staffing, and revenue potential. That is why the solution is built with risk management, data quality, transparency, and human control as part of the product.
Prediction can influence working hours, staffing, and revenue potential. That is why the solution is built with risk management, data quality, transparency, and human control as part of the product.
Prediction can influence working hours, staffing, and revenue potential. That is why the solution is built with risk management, data quality, transparency, and human control as part of the product.
Risk management and DPIA before use in staffing decisions.
Data governance with quality, representativeness, and traceability.
Clear communication about how the AI works and its limitations.
Human-in-the-loop: the customer can override recommendations.
Happy to schedule a time with you
Happy to schedule a time with you
Happy to schedule a time with you
Kenneth Røsseth-Sørensen, Chief Technology Officer, Retail Insight. +47 932 17 552 · retailinsight.no
Kenneth Røsseth-Sørensen, Chief Technology Officer, Retail Insight. +47 932 17 552 · retailinsight.no
Kenneth Røsseth-Sørensen, Chief Technology Officer, Retail Insight. +47 932 17 552 · retailinsight.no
©2026 Retail Insight AS. All rights reserved.
©2026 Retail Insight AS. All rights reserved.
©2026 Retail Insight AS. All rights reserved.