Nutralike Admin Dashboard
A nutraceutical quotation engine that takes a product brief, prices every ingredient, and delivers a PDF-ready B2B quote in minutes. No spreadsheets. No manual unit math.
02CONTEXT
Client snapshot
Nutralike Formulation manufactures nutraceutical products: powders, capsules, effervescent tablets, and more. Their sales and operations teams needed one place to price ingredients, build quotes, and send consistent documents to B2B buyers.
Industry
Nutraceutical B2B
Product
Admin Dashboard
Stack
Next.js + REST API
Pricing Model
Per-KG ingredients
The goal was simple: go from product brief to priced ingredient breakdown to formal quotation to PDF. Database-backed pricing for known materials. AI assistance when an ingredient is not in the master list. Packaging costs folded in. MOQ editable after the quote goes out.
03 / OPERATIONAL CONTEXT
Legacy Friction
Problem statement
Nutraceutical quotes are detail-heavy. Dozens of raw materials priced per kilogram. Batch sizes in grams. Packaging that changes by jar size and cost tier. One wrong conversion and the whole quote is off.
Overhead Summary
Hours per quote
spent on lookups, conversions, and reformatting before a client even saw a number.
Legacy Process Flow
Copy-paste ingredient lists from Excel or PDF specs
Manual price lookup for every raw material line
g to KG mistakes that skewed totals
Full re-quote when a client changed MOQ
Critical Bottlenecks
Manual Price Lookups
Sales staff pulled ingredient rates from scattered spreadsheets and old PDF specs before every quote.
Unit Conversion Errors
Grams, kilograms, and milligrams got mixed up. Totals were wrong and quotes had to be rebuilt from scratch.
Slow MOQ Re-quotes
When a client changed minimum order quantity, the team redid the full calculation by hand.
Inconsistent Documents
Every salesperson sent a different quote layout. Clients got confused and deals moved slower.
04EXECUTION ROADMAP
How we built the quotation engine
Six phases from ingredient database to live MOQ editing. Open each step to see what shipped and why it mattered for the sales team.
We built a single source of truth for raw material pricing. Every quote pulls from the same live data.
Price per KG storage model
Search, sort, and pagination
Synonym matching for ingredient names
Excel and PDF bulk import
Up to 500 items in the active pool
Administrators maintain one ingredient table. When a price updates, every new quote reflects it automatically. No more hunting through old files.
Step one of the quote flow collects client details, product info, dosage form, MOQ, and packaging choices.
Company, contact, and address fields
Jar or sachet packaging types
Pack weight from materials API
Min and max cost tier selection
Custom dosage form support
Packaging options load from the backend. Sachet pricing locks to the fixed tier. Validation catches bad emails and 10-digit mobile numbers before the next step.
Step two fills the quote line items from a file upload, pasted text, or just a product name.
File upload with pack weight context
Paste formulation text directly
AI fallback from product name only
Database match with word matching
AI-estimated price flag for review
The extract API returns matched ingredients with prices from the database when possible. Unknown items get an AI estimate and a clear badge so the team can override before sending.
Every line item prices per kilogram. The UI handles unit switches without breaking totals.
g, KG, mg, Ltr, ml, oz, lb, pcs units
Qty converts when unit changes
Total stays fixed on unit switch
Total recalculates on qty edit
Rupee-formatted line totals
If someone switches 43,956 grams to kilograms, the quantity becomes 43.956 and the total does not move. This removed the most common pricing mistake in their old workflow.
Step three reviews the breakdown, then generates a formal quotation with wastage, profit, and packaging built in.
Subtotal, wastage, and profit layers
Per-pack and per-KG rate output
Standardized customer document layout
Commercial terms block included
One-click PDF download
The backend returns a full pricing breakdown. The frontend renders a clean document with customer details, product row, GST notes, freight, payment terms, and delivery timeline.
After a quote is saved, only MOQ stays editable. Change it and the total recalculates server-side.
Pencil edit on detail page
PUT endpoint for MOQ updates
Total amount refreshes from API
Session cache as offline fallback
PDF re-download with new figures
Repeat customers often tweak order size. Instead of rebuilding the quote, the team updates MOQ in place and sends a fresh PDF in seconds.
Strategic Architecture
System flow & mind map
Product Thinking Process
We mapped how Nutralike actually quotes today before writing a single screen. Each phase tied back to a real sales workflow step.
Empathize
- Sales team interviews
- Spreadsheet audit
- Quote format review
›››
Define
- Per-KG pricing rules
- Unit conversion map
- PDF document spec
›››
Ideate
- DB + AI hybrid matching
- Smart unit switching
- MOQ recalc API
›››
Design
- 3-step wizard flow
- Ingredient autocomplete
- Commercial terms block
›››
Test
- Quote accuracy checks
- MOQ edit validation
- PDF output review
Project Timeline
Core Build & Wizard
PDF, MOQ & Handover
Ingredient Master
& API Layer
Step 1 Wizard
& Packaging API
Extract Pipeline
& Line Item Table
Unit Logic
& Price Recalc
Generate Quote
& PDF Export
MOQ Edit Flow
& Detail Page
Sales Team
Onboarding
1st
Week
2nd
Week
3rd
Week
4th
Week
5th
Week
6th
Week
7th
Week
8th
Week
9th
Week
10th
Week
11th
Week
12th
Week
Business ROI
Impact by the numbers
3 Steps
Quote Wizard
Customer to PDF
Minutes
Turnaround
Not hours per quote
500+
Ingredients
Live price database
1 Click
MOQ Update
Server-side recalc
"
Quotes that used to take half a day now take ten minutes. Ingredient prices live in one place, and when a client changes MOQ we recalculate on the spot.
N
Sales & Operations Team
Nutralike Formulation Pvt. Ltd.