Stop Guessing How Many Bagels to Bake Tomorrow. Know Exactly What to Produce.
Bagel bakery production software that tracks orders, forecasts demand, and tells you exactly what to boil and bake each shift — so you stop throwing away day-olds and missing walk-in sales.
Forecast daily demand within 15 bagels of actual sales. Cut day-old waste by 40%. Never miss a walk-in order again.
You're at 3 AM on Friday, pulling trays of boiled bagels out of the proofer. You guessed you'd need 180 plain bagels today. By 2 PM, you've sold 240, and a catering order for 100 came in at lunch. You had to turn them down. Monday, you made 160 plain bagels. You threw out 47 at close. No spreadsheet, no notebook, no gut feeling is giving you the right number. Bagel bakery production software exists to solve exactly this — to show you what to bake based on what actually sells, not what you hope sells.
Free 14-day trial. No credit card required.
Sound Familiar?
“You're baking blind — guessing at quantities every morning”
You start boiling at 4 AM. By 5:30 AM, you've already committed to 200 plain bagels, 80 everything, 60 sesame. You don't know if that's right. Wednesday you made 280 bagels and sold 210. Thursday you made 220 and could have sold 300. You're trading between waste and missed sales, and you have no way to know which mistake you'll make today. This costs you $40–80 a week in unsold inventory and an unknown number of lost orders.
“Your inventory spreadsheet doesn't talk to your order book”
You have 14 kg of cream cheese in the walk-in. You think. You also have 8 bagel orders for tomorrow that need 2 kg each. That's 16 kg. You won't know until your baker tries to make the third order and tells you you're short. By then it's too late to reorder. You end up buying emergency cream cheese at retail price, or you call customers and cancel. Both hurt.
“You can't tell which bagel varieties actually make money”
Plain bagels sell 40 a day. Everything bagels sell 25 a day. Pumpernickel sells 8 a day. You charge the same price for all of them. But pumpernickel uses specialty flour that costs 3x more. You're losing money on every batch. You don't know this because you've never costed out a single recipe. You just know you're not making as much as you should be.
“Your staff shows up and doesn't know what to prep”
Your baker arrives at 4 AM. You're not there yet — you're coming in at 6. He doesn't know how many bagels to boil, what fillings to have ready, or whether today is a 300-bagel day or a 150-bagel day. He starts boiling the usual amount. You arrive, see the orders, and realize he's made the wrong call. Now you're stressed, he's frustrated, and the bagels are already in the water.
“Friday and Saturday are chaos. You have no way to staff for demand.”
Friday you need 3 people on shift. Saturday you need 4. You schedule 3 people for both days because you don't know the difference. Friday your team is bored and standing around. Saturday you're drowning, customers are waiting 20 minutes for a dozen, and quality drops. You lose money both ways — overstaffing or understaffing.
Your Production Schedule Writes Itself Based on Real Orders
Monday morning you open the app. It tells you: 'Boil 210 plain, 68 everything, 52 sesame, 40 asiago. You have 6 confirmed orders plus 15 walk-ins from last Friday.' Your baker sees the same list on his phone. He knows exactly what to prep. Your inventory system flags that you're 2 kg short on cream cheese and tells you to reorder by Wednesday. By noon, you've already sold 180 bagels and taken 3 walk-in orders. The system adjusts Friday's forecast automatically. You're not guessing anymore. You're responding to what customers actually want.
- ✓Demand forecasting learns from your sales history — shows what to bake each day based on what sold last week
- ✓Inventory alerts tell you when cream cheese, flour, or toppings hit reorder point — 48 hours before you run out
- ✓Staff sees the bake list on their phone — plain bagels, boil time, portion size, what's needed by 6 AM
- ✓Order-to-production pipeline tracks every bagel from inquiry to sold — no order falls through the cracks
- ✓Cost per dozen calculates automatically — you know if pumpernickel is profitable or if you need to raise the price
How It Works
Enter your recipes once. BakeOnyx calculates the cost per bagel.
You log in and add your plain bagel recipe: 2 kg bread flour ($1.20), 200g honey ($0.80), 50g salt ($0.10), 1.2L water (free). Total cost per batch: $2.10 for 24 bagels. That's $0.0875 per bagel. You add your everything bagel recipe: same base dough plus $0.35 in everything seasoning. Now it costs $0.12 per bagel. You can see instantly that everything bagels cost more to make but you're charging the same price. You raise the price 50 cents. You just added $12 per day in profit.
Link your orders to your recipes. The system shows what to bake.
A customer orders 24 plain bagels for pickup Friday. You click 'confirm order.' The system adds 24 plain bagels to Friday's production schedule. By Thursday night, you have 3 confirmed orders (72 plain, 36 everything, 24 sesame) plus historical data showing you sell 40 plain walk-ins on Friday mornings. The system recommends: boil 150 plain, 50 everything, 35 sesame. Your baker sees this list at 4 AM. He boils exactly that amount. No guessing.
Track what actually sells. The system learns and adjusts.
Friday you boil 150 plain bagels. By 3 PM, you've sold 148. You had 2 left. Saturday the system sees this and recommends 160 plain for Sunday (based on your typical Sunday walk-in traffic). You boil 160. You sell 158. The system is now predicting your demand within 2-3 bagels. Over 4 weeks, your waste drops from 47 bagels a week to 8. That's $35 a week you're not throwing away.
Get inventory alerts before you run out.
You have 8 kg of cream cheese. Thursday's orders need 6 kg. That leaves 2 kg for Friday walk-ins. The system sends you a message Wednesday morning: 'Reorder cream cheese by Thursday. You'll be short by Friday.' You place an order. It arrives Thursday afternoon. You never call a customer and cancel because you're out of stock.
Your staff knows what to do before they arrive.
Your baker gets a notification at 3:45 AM: 'Today's bake list: 150 plain (boil 5 min), 50 everything (boil 5 min), 35 sesame (boil 4 min). Confirmed orders: 3. Expected walk-ins: 18.' He opens the app, sees the quantities, and starts boiling. No phone call. No confusion. He's already working on the right thing when you arrive.
Stop Wasting Bagels. Start Baking Based on Real Demand.
Try BakeOnyx free for 14 days. No credit card required. See your first demand forecast by tomorrow morning.
Before & After BakeOnyx
Deciding how many bagels to boil on a Friday morning
Before
It's 4 AM. You're at the mixer. You think: 'Last Friday I made 280 and sold 210. This Friday might be busier. I'll make 300.' You boil 300 bagels. By 2 PM, you've sold 240 and have 60 sitting in the bin. By 5 PM, you've sold 250 total. You throw away 50 bagels. That's $37 in waste. Your baker is frustrated because he boiled for 3 hours and most of it went in the trash.
After
It's 4 AM. Your baker opens the app. It says: 'Boil 260 plain, 70 everything, 45 sesame. Historical walk-ins: 35. Confirmed orders: 28.' He knows exactly what to do. By 2 PM, you've sold 245 bagels. By 5 PM, you've sold 268. You have 12 left over. That's $8 in waste. Your baker finished boiling by 5:30 AM instead of 7 AM, so he had time to help with other tasks. You made an extra $29 that day just by baking the right amount.
A catering company calls Friday asking for 100 bagels
Before
It's 11 AM. A catering company calls: 'We need 100 plain bagels by noon for a corporate event.' You check the counter. You have 23 plain bagels left. You sold out of plain at 10:30. You tell them no. They hang up and call another bagel shop. You lose the order. $75 in revenue, gone. Your baker wonders why you didn't forecast this and bake extra.
After
It's 11 AM. The same catering company calls. You check the app. You have 87 plain bagels in inventory (you forecasted accurately and baked 260 this morning). You say yes. You bag up 100 bagels, they pick up at noon, you charge $75. You also sold 160 walk-in bagels that day. You didn't have to turn anyone away. Your baker baked the right amount, and you captured the order.
Tax season arrives and you need to know your food costs
Before
It's January 15. Your accountant asks: 'What were your food costs for 2024?' You have no idea. You have some credit card statements, some handwritten receipts, and a vague sense that you spent a lot on flour and cream cheese. You spend 6 hours digging through bank statements and supplier invoices. You come up with a number that feels wrong. Your accountant files your taxes with incomplete data. You might be overpaying or underpaying. You won't know until April.
After
It's January 15. Your accountant asks the same question. You click 'Reports' → 'Supplier Spend by Month' → 'Export to Excel.' One click. You have a complete breakdown: flour spend, cream cheese, toppings, packaging, everything. Sorted by month, by supplier, by product. Your accountant files accurate taxes. You know your actual food cost percentage (should be 28–35% for bagels). You can see which months were high-cost and why. You file on time with confidence.
Your baker calls in sick on Saturday morning
Before
It's 4:45 AM on Saturday. Your baker texts: 'I'm sick, can't come in.' You panic. You have no list of what needs to be baked. You have no idea how many bagels to make. You call your assistant. She doesn't know either. You end up boiling 180 bagels based on a vague memory of last Saturday. You run out by 11 AM. Customers are angry. You're stressed. Your assistant is frustrated because she's doing work she's not trained for. You lose $60 in sales and spend the whole day in crisis mode.
After
It's 4:45 AM on Saturday. Your baker texts: 'I'm sick, can't come in.' You open the app on your phone. It says: 'Saturday bake list: 240 plain, 85 everything, 60 sesame. Confirmed orders: 12. Expected walk-ins: 42.' You call your assistant. You send her a screenshot. She knows exactly what to do. She starts boiling the right amounts. You arrive at 6 AM to find the first batch already cooling. By 11 AM, you've sold 285 bagels. You have 80 left for the afternoon. Everything runs smoothly. You're not stressed. Your assistant feels confident because she had clear instructions.
What Changes for You
Cut bagel waste by 40% — stop throwing away day-olds
Most bagel shops throw out 15–25% of daily production. You're losing $50–120 a week to stale bagels. When you bake based on actual demand instead of a guess, you match supply to sales. Over a month, you'll cut waste from 47 bagels a week to 8–12. That's $140–180 a month back in your pocket. For a shop making $8,000 a week in bagel sales, that's a 2.1% margin improvement.
Never miss a walk-in order or catering call again
You can't sell what you haven't baked. When you forecast accurately, you have the right mix of flavors ready. A catering company calls Friday asking for 100 bagels by noon. You have 87 plain and 18 everything ready to go. You make the sale. Last month, you turned down 3 orders because you'd already sold out. That's $240 in lost revenue. With accurate forecasting, you capture those sales.
Know your exact profit per dozen — adjust prices in real time
You discover pumpernickel costs you $1.44 to make but you're charging $8 per dozen (same as plain). Plain costs $2.10 for 24 bagels ($0.0875 each, or $0.70 per dozen). You're underpricing pumpernickel by $0.50 per bagel. Raise the price to $9 per dozen. You just added $4–6 per day in profit (if you sell 8–12 pumpernickel bagels). That's $120–180 a month.
Staff scheduling becomes data-driven, not a guessing game
You see that Friday needs 320 bagels and Saturday needs 380. Friday you schedule 2 bakers. Saturday you schedule 3. Your labor cost drops because you're not overstaffing slow days or understaffing busy ones. You also cut stress — your team isn't drowning on Saturday or bored on Friday. Retention improves. One new hire costs $2,000 in training. Keeping your current team happy is worth it.
Reorder inventory 48 hours early — never pay emergency prices
Cream cheese is $8 per kg at your distributor. At the corner store, it's $14. When you run out and have to buy retail, you're paying a 75% premium. The system tells you Wednesday that you need cream cheese by Friday. You order from your distributor. You save $6 per kg. If you buy 20 kg a month, that's $120 in unnecessary costs you eliminate.
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Stop Wasting Bagels. Start Baking Based on Real Demand.
Try BakeOnyx free for 14 days. No credit card required. See your first demand forecast by tomorrow morning.
Free 14-day trial. No credit card required. Plans from $29/month.