Pricing drift between reps
Different reps were quoting different terms for similar work because pricing lived in scattered spreadsheets and old proposal files rather than one governed source.
AI SAAS MVP CASE STUDY
A proposal generator that only quotes what the company actually sells
Sales teams needed to turn service scopes and customer requirements into structured proposals fast, without a generator that guesses at pricing. We built an MVP that pulls exclusively from an approved services and pricing catalog, then routes every draft through a human review step before it reaches a customer.
▣ Catalog-locked pricing Every quoted line item traces back to an approved rate, never a model guess
♙ Mandatory review gate No proposal reaches a customer without a human sign-off step
✦ Structured output Consistent sections for scope, pricing, terms and timeline on every draft
Proposals that stay inside the lines the business already approved
Services businesses that quote custom work face a specific risk with AI drafting tools: a fluent-sounding proposal that quietly invents a discount, a service tier, or a payment term nobody signed off on. That risk grows with every new rep who uses the tool and every catalog update the tool doesn't know about.
The MVP was scoped around removing that risk rather than around making proposals sound better. The generator treats the approved services and pricing catalog as the single source of truth, assembles proposals only from what's in it, and flags anything a rep asks for that isn't in the catalog instead of inventing a plausible substitute.
▥IndustryProfessional Services / AI SaaS
◇ProductAI-assisted proposal generator with catalog-locked pricing
♙AudienceSales and business development teams issuing custom quotes
⌁Delivery[CONFIRM TIMELINE]
The Challenge
No checkpoint before sending
Draft proposals could go straight from a text box to a customer's inbox, with no structured point where someone checked the numbers or terms.
Templates that didn't scale with catalog changes
Static templates meant every pricing update or new service line required manually editing multiple proposal documents instead of updating one source.
What We Can Identified
A proposal workflow that treats the catalog as law and treats a person as the last word before anything ships.
Catalog-bound pricing lookup
Reps select services from the approved catalog rather than typing prices, so every line item a customer sees matches what finance has actually authorized.
Requirement-to-scope mapping
Customer requirements are matched against catalog service descriptions, so the generated scope section reflects what the business actually delivers, not a generic paraphrase.
Unmatched-request flagging
When a customer asks for something outside the catalog, the draft flags it for a human decision instead of fabricating a price or scope to fill the gap.
Structured proposal sections
Every draft follows the same scope, pricing, terms and timeline structure, so customers get a consistent read regardless of which rep sent it.
Mandatory review-before-send step
No proposal can be marked ready to send until a designated reviewer has opened it and approved the numbers, closing the gap between drafting and sending.
Version history per proposal
Each edit and review decision is kept against the proposal record, so managers can see who changed what before a document went to a customer.
How MVPHUB Delivered It
1
◇ Catalog Audit
We reviewed how the company's services and pricing catalog was actually maintained, so the generator could read from one governed source instead of scattered files.
2
✎ Guardrail Design
We defined exactly what the generator was and wasn't allowed to invent, building the unmatched-request flag before writing the drafting logic itself.
3
✦ MVP Build
We built the catalog lookup, requirement mapping, and structured drafting flow as one connected pipeline rather than separate disconnected steps.
4
♢ Review Gate Integration
We added the mandatory human review checkpoint as a first-class step in the workflow, not an optional afterthought reps could skip.
5
⌁ Rep Validation
We ran real proposal scenarios past sales reps to confirm drafts matched catalog terms and that the review step fit how they actually worked.
Every number in a proposal can be traced back to an approved catalog entry, not a generated guess.
Engineering Behind The Experience
Single source of pricing truth
The generator reads pricing and service definitions from one governed catalog structure, avoiding the drift that comes from duplicated data.
Review state as a workflow stage
Proposal status moves through explicit draft, review, and approved stages rather than a single free-text document with no gate.
Auditable drafting
Each generated section is linked back to the catalog entry or requirement it came from, so a reviewer can verify a claim rather than just trust it.
The Outcome
Before: Manual, inconsistent quoting
× Reps re-typed prices from memory or old documents
× No single place held the current approved pricing
× Proposals could be sent without anyone else reviewing them
× Formatting and structure varied proposal to proposal
After: Governed, review-gated proposals
✓ Pricing pulled directly from the approved catalog every time
✓ Requirements mapped to real service scope automatically
✓ Every proposal passes a review step before it reaches a customer
✓ Consistent structure across scope, pricing, terms and timeline
What This Means For The Business
Sales reps draft proposals faster without touching pricing directly
Leadership gets a consistent review checkpoint on every quote
Fewer pricing disputes trace back to inconsistent proposal terms
Speed without giving up control over what gets promised
The goal was never a faster way to write proposals — it was a faster way to write proposals that couldn't drift from what the business actually approved.
By binding the generator to the catalog and keeping a human as the last checkpoint before sending, the MVP gave the sales team speed without asking anyone to trust an AI-invented number.
THE MVPHUB PRINCIPLE
"Speed is only useful when it's speed toward something true — a proposal generator should accelerate approved facts, never invent new ones.
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Building a proposal tool your reps can actually trust?
We help teams design AI drafting tools that stay bound to approved data and keep a human in the loop where it matters. Let's talk about your proposal workflow.
AI-accelerated. Expert-verified. Built around the outcome your first release needs to prove.
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