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OptimaBrainAI order recommendations
The right quantity.
On every visit.
OptimaBrain analyzes each store's history and returns an accurate quantity recommendation in under 200ms - with an explanation of why, not a black box. The rep accepts or adjusts with one tap.
<200msper recommendation
24months of history
1tap to decide
Order · "At Ivan's" storeINDIRECT
Water 1.5L PETPromo
Recommendation
42бр
7 packsWhy this quantity
Active promotion +22%
Seasonal peak (May) +18%
Friday pre-weekend +5%
Confidence 0.83
Water 0.5L
242 packs
Sparkling 1.5LTrend
183 packs
Orange juice 1L
121 pack
One decision
Everything about the store becomes one number
Sales, stock on hand, promotions, weather, field visits, and assortment - OptimaBrain analyzes them together for every store and returns the exact order quantity, with the reasoning why.
Sales (sell-out)
Stock on hand
Active promotions
Season & weather
Field visits
Must-stock assortment
OptimaBrainRecommendation for the store
Exact quantity for the storeWhy this muchSignals and warningsLearns from the outcome
One recommendation, dozens of factors
For every store OptimaBrain weighs sales history, season and temperature, active promotions, stock on hand, and trend - and distills them into one precise quantity.
Nothing hidden behind a recommendation
You see how the number is reached - which data goes in, how business rules combine with learning from your own history.
Active promotion +22%
Stockout last week
Seasonal peak (May) +18%
Below target assortment
Friday pre-weekend +5%
Upward trend over 3 visits
Active promotion +22%
Stockout last week
Seasonal peak (May) +18%
Below target assortment
Friday pre-weekend +5%
Upward trend over 3 visits
Explains every recommendation
In plain language you see why this exact quantity - stockout, seasonal peak, active promotion, trend.
Learns on its own, gets more accurate
It checks every recommendation against real sell-out and retrains every week. Accuracy grows over time, with no manual tuning.
How it works
From visit to decision in a fraction of a second
Without changing the rep's habit. They open the store, see a recommendation, confirm.
01
Open the store
The rep opens the store in the SFA app. OptimaBrain receives a request behind the scenes.
02
Engine computes
Business rules on the history and learning from context - promotions, season, stock - work together in under 200ms.
03
Recommendation with reasoning
Returns the quantity, how confident it is, and a clear why.
04
Accept and the system learns
The rep accepts or adjusts with one tap. The outcome feeds back into the model.
Not a black box
Two layers that work together
Transparency and safety from the business rules, personalization from learning on your own data. Everything works within safe bounds - never an unpredictable recommendation.
Layer 1
Business rules
How much sells and on what cycle, what buffer to keep, mandatory assortment, and a quantity ceiling. Transparent and predictable.
- Sell-out rate from history
- Buffer scaled to variability
- Mandatory minimums and limits
Layer 2
Machine learning
A model trained on 24 months of your history. It learns how this exact store responds to promotions, season, temperature, and day of week.
- Promo impact for each store
- Seasonal and temperature swings
- Kept within safe bounds
How the recommendation is built
Base quantity (history + buffer)28
Learning adjustment (promo + May + Friday)× 1.47
Rounding to full pack→ 42
Smart Insights
A sales coach in the rep's pocket
Up to 5 actionable insights with every recommendation. Not just a number, but arguments for the conversation with the store.
WARNING
Anomaly or risk
Demand is 2× above the historical maximum
PATTERN
Chronic trend
Stockout in 87% of visits
CONTEXT
External factor
Forecast +32°C - heat wave this weekend
ACTION
Suggestion
Discuss increasing capacity with the distributor
Results
Numbers from the FMCG industry
Documented benchmark ranges for AI recommendation systems in the first 12 months after go-live.
+8-15%More sales
−20-30%Fewer stockouts
−15-20%Less overstock
80-90%Rep adoption
Industry benchmark targets (McKinsey, BCG, RELEX), not guarantees. Your specific KPIs are finalized after analyzing your real data.
Give us the history. We'll return a decision
Book a demo and see OptimaBrain on your own real store and sales data. Connects to your SFA or runs standalone.