AI Quotation Generator
We build quotation systems that can read product information, extract attributes, and assemble accurate quote drafts much faster than manual workflows.
Typical impact
Based on similar deployments. Actual results depend on your workflow and data.
When to choose this
- Sales teams quoting from product photos or messy specs
- B2B sellers with repeatable pricing rules
- Wholesale or catalog businesses with SKU complexity
Is this solution for you?
A quick check before you invest time in a call — who gets the most value, and when to pick something else.
Good fit if you…
- Sales teams quoting from product photos or messy specs
- B2B sellers with repeatable pricing rules
- Wholesale or catalog businesses with SKU complexity
- Teams where quote turnaround loses deals
Probably not if you…
- Every quote is a custom legal contract from scratch
- No pricing rules — prices invented per deal with no structure
- Products that cannot be described from image or structured fields
Before vs after
What actually changes in day-to-day operations — not marketing fluff.
Data entry
Today
Retype attributes from photo into ERP
With this solution
Extraction into editable draft
Pricing errors
Today
Wrong tier from spreadsheet typo
With this solution
Rules engine on every line
Turnaround
Today
Quote sent next day after internal chase
With this solution
Draft in minutes, human approves
Consistency
Today
Two reps quote the same SKU differently
With this solution
Same rules, same format
How a request moves through the system
Vision or structured extraction fills attributes. Business rules handle price. A draft quote is generated for sales to edit and approve before the customer sees it.
Sales uploads image or selects product attributes
Vision or parser fills SKU, dimensions, options
Business rules apply discounts, tiers, and tax
PDF or branded quote document generated
Sales edits lines, terms, or margin before send
Customer receives approved quote; CRM updated
Real scenarios
Concrete situations this solution is built to handle — not generic feature bullets.
A photo from the warehouse floor
Sales uploads the image, gets attributes filled, and reviews a draft quote instead of typing SKU fields from memory.
A repeat product with a pricing rule
Once rules exist, the same item does not get a different price because someone rounded in a spreadsheet.
A quote that needs a human tweak
The salesperson adjusts terms, then sends. AI skipped the data entry, not the relationship.
What we build
- Image and data extraction
- Auto-generated quotation drafts
- Pricing rule integration
- Approval and edit flow
- Faster turnaround for B2B quotes
- Consistent drafts for sales review
Outcomes you can expect
- Faster quote turnaround
- Less manual product data entry
- Pricing stays on business rules
- Sales keeps final approval before customer sees it
Connects with
Common use cases
- · Sales quoting automation
- · E-commerce quotation workflows
- · B2B product estimation
- · Fast proposal creation
How we typically deliver
Phases and outputs so you know what happens week by week. Timelines adjust to your scope.
Week 1–2
Sample products, pricing rules, and quote template
You get: Extraction workflow design
Week 3–4
Vision + rules + draft UI
You get: MVP on staging catalog
Week 4–5
Sales review flow and CRM hook
You get: Pilot with one product line
Week 5+
Expand SKUs and measure error rate
You get: Quality checklist
Common questions
Does the AI set the final price?
No. The system extracts product details and applies your pricing rules to draft a quote. Sales can edit line items, discounts, and terms, then approve before the customer sees anything. That keeps commercial control with your team while removing re-keying and missed configuration details. Pricing logic stays yours—tables, margins, bundles, and approval thresholds. We design the workflow so AI accelerates draft creation without becoming an unsupervised discount engine.
What is the input — only images?
Images are a common bottleneck when sales receives photos of products, specs, or handwritten notes. The same pattern can also take structured fields, PDFs, or CRM inputs when they already exist. We design intake around how quotes actually arrive today, not an idealized form. Extraction confidence flags uncertain fields for human review before pricing runs. Over time, cleaner structured intake can reduce reliance on messy media. The goal is fewer quote cycles delayed by missing or misread details.
Is this a full CPQ suite?
It is a focused quote-generation workflow for faster, more accurate drafts in your current sales process—not a rip-and-replace of an entire CPQ stack on day one. If you already have CPQ, we can complement it; if you do not, this often unlocks immediate relief on high-friction quote paths. Scope typically includes extraction, pricing rules, review, and delivery of a draft quote artifact. Broader CPQ concerns like enterprise catalog governance can be phased later. We keep the first release tied to measurable quote turnaround improvement.
Can this be extended to other product lines?
Yes. Extraction patterns, pricing rules, and the approval step are the reusable pieces. New product lines usually need additional examples, rule tables, and review thresholds rather than a brand-new architecture. We document how to add SKUs and configurations so sales ops can expand coverage. Pilots often start with one product family where quote errors or delays hurt most. Once stable, adjacent lines follow the same blueprint with less ramp-up time.
Shipped in production
Related case study
AI Quotation Generator
An AI MVP that turns product images into accurate price quotations using extraction and business pricing rules.
Read the full case studyOther solutions
Reduce support load
Customer Support Automation
Coordinate specialist agents
AI Multi Agents
Natural voice interactions
Voice AI Agents
Want this mapped to your workflow?
We will walk through your tools, volume, and escalation rules — and tell you honestly if this is the right fit.
Book a consultation