Transfer Reports
Select stores and date to load transfer orders
Stores
Mode
Date
Purchase Analytics
Select branches and date range to load purchase orders
Stores
Mode
Date
Fulfillment Status
Purchase Heatmap — Branch × Category
GRN Analytics
Select branches and date range to load Goods Received Notes
Stores
Mode
Date
Status
GRN Heatmap — Branch × Category
Sold Out Items
Select branches and fetch to see currently sold-out items
Branches
Category
Search (name / SKU)
📊 Stock Availability Heatmap — Branch × Category
All Clear
<15%
15–30%
30–60%
>60%
🏪 Branch Availability Overview
⚠️ Category Risk Summary
📋 Sold Out Item Detail
| # | SKU | Branch | Category | Short Name | Long Name | Sold Out Time | Out Duration | Marked By |
|---|
Current Stock
Select stores and fetch to see live inventory levels, heat maps, and stock movement.
Stores
Category
Status
Search (name / SKU)
Total Items
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Out of Stock ↗
—
Low Stock ↗
—
In Stock ↗
—
Overstock ↗
—
Negative stock ↗
—
Stock Value
—
📋 All Stock
🌡 Heat Map
📈 Movement
🛒 Order List
| SKU | Item Name | Store | Category | Qty | Unit | Avg Cost | Stock Value | Status |
|---|
🌡 Stock Health Heat Map
100% Healthy
>75%
50–75%
25–50%
Critical
Overstock
Inventory Adjustments
Select stores and date to load adjustment records
Stores
Mode
Date
Inventory Audit
Select stores and date, then fetch audit records
Stores
Mode
Date
From
To
Status
Audit Sessions
By Category (Amount)
By Branch (Amount)
Top Items by |Variance|
Session Status
Variance Heatmap
Audit item log
| Order # | Business Day | Time | Branch | Status | Item | SKU | Category | Sub-Category | Unit | Audit Qty | Variance | Unit Cost (₹) | Amount (₹) | Overridden | Batch # | Expiry |
|---|
Item Totals
| Item | SKU | Category | Branch | Total Audit Qty | Unit | Total Variance | Avg Unit Cost (₹) | Total Amount (₹) | # Audits |
|---|
Activities
Track inventory losses, actual food cost, and sold-out events — all sourced from Rista item activity sync
Inventory Store
From
To
⚠
Date range or branch changed — the data below is from a previous fetch. Click Fetch to refresh.
♻
No data loaded yet
Pick one or more inventory stores and a date range, then click Fetch to load item-wise activity, wastage and stock movement — pulled live from Rista per store.
Data is fetched directly from Rista's item-activity API for each selected inventory store — so base kitchens and warehouses work too, not just sales branches.
Item Activity
One row per item per store — opening/closing balance and every movement (in, sold, transfers, loss) over the selected range.
🔍
| # | Store ⇅ | SKU | Item ⇅ | Category ⇅ | Unit | Opening ⇅ | In ⇅ | Sold ⇅ | Out ⇅ | Loss ⇅ | Adj ⇅ | Closing ⇅ | Loss ₹ ⇅ |
|---|
No item activity returned for the selected store(s) and date range.
Activity types recorded by Rista: Sales (deducted from stock when sold) · Purchase/Transfer In (stock received) · Wastage/Damage/Shrinkage (stock losses) · Voided (reversed transactions).
Negative cost = stock was removed from inventory.
Cost by Activity Type
Opening vs Closing Stock Value
All Activity Types
Aggregated across all branches and days in the selected range. "Active Days" = distinct calendar days with that activity type recorded.
| # | Activity Type | Net Qty | Total Cost (₹) | Active Days | Unique SKUs |
|---|
No activity data. Run an Item Activity sync for this date range first.
Search SKU
🔍
🔍
SKU Stock Card
Search for an ingredient or item above to see its full daily balance, opening/closing costs, and every activity recorded against it — purchases, transfers, sales, wastage — across the selected date range.
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Daily Balance
Opening and closing stock quantity and cost for each day with synced data. Days not yet synced are not shown — use Sync this range if rows are missing.
| Date | Branch | Opening Qty | Opening Cost (₹) | Closing Qty | Closing Cost (₹) | Qty Change |
|---|
Activity Lines
Every inventory movement recorded against this SKU: purchases, sales, transfers, wastage, etc.
| Date | Branch | Activity Type | Qty | Cost (₹) |
|---|
Suppliers
Supplier catalogue, price comparison, and item-level sourcing data synced from Rista
Click ↓ Load to sync and display supplier data.
Top SKU Price Spreads — % variance between cheapest & most expensive supplier
Items per Supplier — coverage share
Supplier Coverage — unique SKUs stocked per supplier
Price Tier Heatmap — items per price band per supplier
💰 Savings Opportunities — ranked by ₹ saved per unit by switching to cheapest supplier
| Item / SKU | Suppliers | Best (₹) | Worst (₹) | Save / Unit | Spread % | Cheapest Supplier |
|---|
| Supplier | Code | Contact | Phone | GSTIN | Payment Terms | Credit Limit |
|---|
| Item / SKU | Supplier | Unit Price | MRP | MOQ | Qty/Pack |
|---|
SKUs sourced from 2+ suppliers — ranked by price spread. Click ⊕ Compare to see a side-by-side supplier breakdown with savings callout.
| Item / SKU | Suppliers | Best (₹) | Worst (₹) | Avg (₹) | Price Range | Spread % | Cheapest Supplier |
|---|
Items for supplier
| Item | SKU Code | Unit Price | MRP | MOQ |
|---|
Indent Intelligence
Indent recommendations per outlet: Projection forecast → recipes → live stock and in-transit → whole packs. Review, edit on the pack grid, approve, then send to Rista.
Recent runs
Pick an outlet.
Forecast accuracy
WAPE / MAE / bias of the ingredient forecast against Rista's recipe deduction, last 7 days. Run it.
Settings — safety stock, coverage, pack rules, calendar
Loading…
Vendor Price Intelligence
What each supplier actually charged per inventory unit, from Rista goods-received notes — not catalogue prices.
Loading prices…
Sale Analytics
Select branches and period, then fetch live data
Branches
Period
Channel
Sale Detail
Select a branch and date to load all sales records with full item, payment and customer detail
Branches
Mode
Date
Status
Customer Segmentation
Load customers to segment by loyalty tier and membership status
Customers modified after
Customer Retention
Load customer data to analyse loyalty tiers, churn risk and retention patterns
Load customers modified after
Customer base
Click a segment to filter everything below
Customers
Revenue
Cohort retention
Of everyone who first bought in a given month, the share who came back in each later month.
Visit frequency
Customers by lifetime visit count, with the revenue each band contributes.
Sales Pattern
Fetch a date range to analyse session-wise sales patterns and peak footfall periods
Branches
State
From
To
📍 Weather City
ℹ
Tip: Analyse up to 90 days at once. Wider ranges give the seasonal model more data and improve forecast accuracy. Recommend 30–60 days for daily patterns, 60–90 days for reliable DOW seasonality. Revenue Forecast always projects into the future only — never re-plots past dates.
📈 Branch Revenue Trend (Net ₹ per day)
📊 Combined All-Branch Trend
Sum of all selected branches per day
🗺️ State Performance
Rollup per state · click a card to filter the tab to that state
🚚 Channel Revenue Trend (Net ₹ per day)
One line per channel · respects the branch/state/date filters · legend toggles lines
🔢 Channel × Branch Matrix
▸ Show
🎯 Revenue Forecast & Alerts
Alert threshold:
📅 Weekly Seasonality Pattern
Day-of-week revenue index — 1.0 = average day. Values >1.0 are above-average. 🟠 = weekends.
📉 Revenue Forecast — Next 7 Days
Projected Daily Revenue
| Date | Day | Projected Net (₹) | vs. Avg Actual | Seasonal Idx | Confidence | ☁️ Weather |
|---|
🕐 Hourly Revenue Breakdown
Operating hours (8 AM – 3 AM) · binned by IST clock hour from Rista /sales/page
Hourly Breakdown
| Hour | Orders | Revenue (₹) | Avg Sale (₹) |
|---|
📈 Revenue & Orders Trend
Current period vs previous period of the same length
🛵 Channel-Wise Sales Intelligence
Revenue, orders, AOV, and discount per channel — classified from Rista channelSummary
🏆 Outlet Performance
Ranked by net revenue · growth vs previous period · order volume · efficiency
| # | Outlet | Net Revenue | Orders | AOV | Growth | Share | Trend |
|---|
🕐 Revenue & Orders by Hour
Operating hours (8 AM – 3 AM) · current vs previous · IST clock hour from /sales/page
📅 Weekday vs Weekend
Daily revenue averages by weekday/weekend, vs same-length previous period
⚠️ Order Losses by Outlet
Void / Cancel / Non-chargeable counts & ₹ impact · current vs previous period
| Outlet | Void % | vs Prev | Void ₹ | Cancel % | vs Prev | Cancel ₹ | Non-chargeable | NC ₹ |
|---|
🛒 Basket Size Analytics
Average order value, ticket-size distribution, and per-channel basket performance
Discount Summary
Analyse discount transactions, coupon performance and leakage signals across branches
Branches
From
To
ℹ
Note: Powered by Rista's
/analytics/discount/transactions endpoint, paginated per branch per day via lastKey. Range capped at 31 days for responsiveness. Refinement filters below apply client-side without re-fetching.
✨ Alienkind Insights
AI-powered insights from sold-out events — what happened across all your locations
Branches
Period
Priority
✨
Generate insights from your sold-out data
Pick a period, then click Generate Insights to see executive-ready highlights about which items and outlets had the biggest stock-out impact.
✓
No critical insights detected
Your operations look healthy for this period. Try expanding the date range or filter.
Alienkind Observatory / signal feed
Every leak, ranked by what it costs you this week.
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Aperture — signals by class & certainty
◦ inner = unverified◦ mid = probable◦ outer = confirmed
₹ figures are modelled, not booked. Confirmed = detector had complete inputs and the pattern held across the window. Probable = inputs complete but the window is partly unsettled. Unverified = the pattern is real in the data but at least one input is ambiguous, so the figure is an upper bound for triage only. Loss estimates are scoped to active business hours, never full 24-hour projections.
Festival Sales
Lift over a weekday-matched baseline, aligned by festival day rather than calendar date. Festival dates are hand-seeded and panchang-verified — never estimated.
Festival calendarclick a festival to analyse it · dates are seeded per year
Branches
Forecast Period
ⓘ
Category
Top
items
🔮
Sales & Ingredient Projection
Pick a Forecast Period and click Run Projection to get a day-by-day sales plan. The forecast uses your last 90 days of Rista sales — adjusting for day-of-week patterns, holidays, and payday timing — to predict how many units of each item to prep each day.
⏳
Running projection…
✦ Key Insights
📊 Daily Projection Timeline
Bars = units · Line = revenue
| Date | Day | Items Sold | Revenue | ☁️ Weather | Top items for the day |
|---|
| Item | Branch | Category | Proj Items Sold ▼ | Proj Revenue | Avg Daily Sold | Band (Low–High) | Confidence |
|---|
| Ingredient | Unit | Projected Need ▼ | Stock | Gap | Status |
|---|
Forecast
🖨 Print / Export PDF — choose exactly what to print
Day Segment
Sections (tabs) to print
Stores
Dispatch prints one sheet per selected store.
Pick a forecast type (Mon–Thu, Fri–Sun, or Full Week) to generate the demand plan.
Combos (e.g. "X and Y" bundles) are excluded — their items are already counted as individual sales lines.
Intelligence Login
Sign in to access consumption analytics, BOM management and sync controls.
Username
Password
Default: admin / Admin@2024!
🧮 Inventory Consumption Intelligence
Derive material & packaging consumption, food cost, and gross margin from sales + BOM data — chain-wide
Branches
Mode
From → To
🧮
Derive consumption from sales × BOM
Pick a period and click Run Consumption Engine. The system fetches /inventory/items (BOM, packaging variants, material costs) and /analytics/sales/summary (per-SKU sold qty + revenue) for each branch, then computes theoretical material consumption, food cost, packaging cost, COGS, gross profit and margin.
🔬 Material Intelligence — Dependency & Channel Analysis
Pick any material to see every finished item it ships in (BOM vs BOS), per-channel mix, per-outlet share, and estimated consumption.
Pick a material
Type:
Channel:
BOM vs BOS share
Per-channel consumption
Per-outlet consumption
| Sold Item | Used As | Qty / serving | Sold Qty | Contribution | Cost Share | Scope (branches → channels) |
|---|
Pick a material above to see its dependency tree.
📦 Materials — Theoretical vs Actual Consumption
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| Material | Unit | Theoretical Qty BOM × Sold |
Rista Activity API actual |
API Variance Activity − Theory · hover for note |
CSV Sales Qty Upload CSV ↑ |
Unit Cost | Material Cost | Cost Share |
|---|
🧾 Recipe breakdown — sold items vs materials consumed
Click any row to expand the ingredient breakdown. Quantities and costs are theoretical (BOM-derived).
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📊 All sold items — sales × consumption × margin
Comprehensive per-SKU view across the selected period. Click a column header to sort. Use the search box to filter.
| Item | SKU | Qty Sold | Net Revenue | Avg Price | Food Cost | Pkg Cost | COGS | Gross Profit | FC % | GM % | % of Rev | Class |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
🏪 Outlet performance — food cost % & gross margin %
| Outlet | Net Revenue | Food Cost | Pkg Cost | COGS | Gross Profit | Food Cost % | Gross Margin % |
|---|
🛒 Channel breakdown — revenue, attributed consumption & margin
Per-channel food/packaging cost is allocated proportionally to channel revenue share within each branch; aggregator orders carry a +20% packaging-cost weighting to reflect extra delivery packaging.
| Channel | Orders | Net Revenue | Est. COGS | Est. Margin | Margin % |
|---|
✨ Consumption Insights
ℹ
How these numbers are derived
🔥 Kitchen Consumption
Explode every semi-finished / kitchen-prepared item consumed (from Inventory Consumption) into its underlying raw materials, using the in-house recipe master — then aggregate expected raw usage SKU-wise.
Consumption basis
Options
🔥
Explode semi-finished items into raw materials
Pick a period & branches in Inventory Consumption and run the engine — or click Run Engine & Explode here. Every consumed item that matches an in-house recipe (e.g. Harissa Chicken, Fajita Veggies, Cloudy Foam) is broken down — multi-level — to its raw-material consumption.
🧾 Consolidated Raw Material Consumption
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| Raw Material | SKU | Expected Consumption | Share | Used In |
|---|
🍳 Per Semi-Finished Item → Raw Material Breakdown
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🔍 Coverage & Diagnostics
—
click to toggle
⚖️ Expected vs Actual Consumption
Variance = Actual − Expected, valued at Rista's stock cost (the base kitchen's closing unit cost). Outlet: Actual = Opening + Transfers in − Transfers out − Closing; Expected = consumption as per sales (net of returns) + logged shrinkage + voided items + ingredients for HM the outlet makes itself (worked out from the HM's use, like the base kitchen). Base Kitchen (kitchen + its warehouses): Actual = Opening + GRN + received from other stores − Closing; Expected = sent to outlets + used in recipes + shrinkage + R&D + staff meal (items made at the kitchen balance to zero). Positive = over-used.
loading…
Pick a period and press Run. The first run of a month fetches every store-day from Rista (about a minute); settled days are cached after that.
💰 COGS Calculation
Actual COGS = Opening + Received − Wastage − Closing (at cost; closing includes the daily audit) — consumption excluding wastage. Total Cost = COGS + Wastage; Profit = Net Revenue − Total Cost. Compared vs Expected (recipe), with Variance %, Food/Packaging split, and wastage % of sales. Pick Outlets (COGS uses each branch's own outlet store, never its base kitchen) or Base Kitchens & Warehouses (which also subtract Transfers Out, since they ship stock). Single-day periods give the most reliable balances.
⚠ Sign in to Intelligence first — click the Intelligence tab and log in, then come back to COGS Calculation.
Scope
Outlets
Period
💰
Build the period COGS sheet
For the daily check just hit Yesterday — it runs automatically and opens with the 🚨 Daily Watchlist (red = high variance or wastage, ⚪ = no stock count yet) and 🎯 Top Problem Items to fix first. Actual COGS = Opening + Received − Wastage − Closing at cost; Expected = recipe deduction; Variance = the gap a stock count reveals — on days without an Audit it reads ≈0 (“not measured”). Items moving at ₹0 cost are flagged (COGS understated). Base Kitchens & Warehouses are a separate scope.
⚡ Intelligence Platform
|
Signed in as
Recipe / BOM Manager
Map each menu SKU to its ingredient quantities. Used to calculate theoretical consumption.
Recipe Lines
| SKU ID | Ingredient | Qty | Unit | Yield % | Added by | |
|---|---|---|---|---|---|---|
| Loading… | ||||||
Add / Update Recipe Line (admin / manager)
SKU ID
Ingredient
Quantity
Unit
Yield (0–1)
Yield Factor: 0.8 = 80% usable after prep (e.g. 20% trim loss). Use 1 for no loss.
🍳 Production Projection
DAY
METHOD
BRANCHES
‹ Access
🛡 Access Profiles
Named permission templates that control which modules and branches users can access. Assign profiles to users via the Users pane.
Profiles
—
| Name | Role | Modules | Branches | Users | Actions |
|---|
🔐 Access
Manage users, sessions, access profiles and devices for this dashboard.
Users
👤
›
Users
Manage users and access restrictions.
🎫
›
Active Licences
View and manage active sessions.
🛡
›
Access Profiles
View and manage access profiles.
Devices
💻
Coming soon
Devices
Manage devices and access restrictions.
🔑
Coming soon
Device Registration Keys
Manage keys for registering devices.