A quote is arithmetic wearing a sentence.
Most AI quoting tools get this backwards. They let a language model produce the total, which works almost every time and fails in the one way you cannot afford: a plausible wrong number inside a document your client has already accepted. DocuDeal writes the words with a model and calculates every figure in code, from a price list you control.
Five steps, and none of them is building a template.
You describe the deal, or hand over the call
A sentence works. So does a transcript, a set of notes and the spreadsheet they emailed you. There is no form to fill in and no template to have built first. If something material is missing, such as the term or whether onboarding is included, it asks that one question with tappable answers rather than guessing.
It matches your catalog, it does not invent items
Every product you sell carries a price, your cost, a unit, a billing interval, volume tiers and bundles. The model's job is to work out which of those the customer is asking for. It cannot create a line item that is not in your catalog; anything it cannot match is marked to confirm.
Code applies the tier and does the sum
Twenty-five seats crosses into the 25–99 band, so the rate is $48 and not $60. That selection is a lookup, the multiplication is arithmetic, and the 10% partner discount is applied to a subtotal rather than described in a sentence. No language model is involved in producing any figure.
It checks the quote before you send it
A pre-send pass says what is missing, what is risky and what it could not source: a discount past your policy, a term with no end date, a fee mentioned on the call that is not in your catalog. If your rules say a discount over 10% needs a second pair of eyes, it routes there instead of going out.
The client gets a page, not an attachment
They open a link, see the priced table, can toggle optional lines if you allowed it, ask a question and get an answer out of the quote itself, and sign on their phone. You see who opened it, which section they stayed on, and whether it was forwarded.
Which half is the model doing?
This is the only question worth asking a vendor in this category, and most demos are careful not to answer it. A quote is a commercial commitment. The sentence around a number can be rewritten; the number cannot, once it is signed.
The model writes this
- Which catalog items the customer is asking for
- Scope, assumptions and what is excluded
- The covering note and section prose
- How to phrase a payment schedule
Code computes this
- Unit price, cost and billing interval
- Which volume tier applies
- Line and table discounts
- Deposits, recurring intervals and tax
- The subtotal and the total
A worked example, end to end
"Northwind want 25 Pro seats on an annual plan, plus onboarding. They are a partner so give them the 10 percent. Net 45."
| Matched from catalog | Pro seat · annual · volume tiered |
|---|---|
| Tier selected by code | 25–99 band → $48, not the $60 list rate |
| Seats × rate | 25 × $48 = $1,200 per month, $14,400 annual |
| Onboarding | $4,000 one-off, matched from catalog |
| Partner discount | 10% applied to the subtotal in code |
| Margin check | Cost sits beside price, so the discount is measured against margin, not just the total |
| Terms | Net 45 written into the payment section by the model |
The model never saw a multiplication. It chose the items and wrote the language; the arithmetic happened in code against rows you control.
What to look for in any AI quoting tool
Useful whether or not you end up here. Every one of these is something that costs money the first time it is missing.
- Ask whether the model produces the total. If it does, you are trusting a probabilistic system with a commercial commitment.
- Check whether cost is stored beside price. Without it, nothing can tell you what a discount does to your margin.
- Check volume tiers, bundles and recurring intervals are first-class, not something you fake with a manual line.
- Ask what happens to a figure the tool cannot source. The right answer is that it is flagged; the wrong answer is that it is filled in.
- Check there is an approval rule you can set on discount or total, and that it fires before sending rather than after.
- Check the client gets a page they can interact with, not a PDF that tells you nothing about who read it.
- Check quotes can be sent in bulk from a CSV with validation, for the times you are repricing a whole book.
Where AI quoting goes wrong
The plausible wrong number
A model asked to total a quote will be right nearly every time. The failure is not a typo you spot, it is a believable figure inside a document the client has signed, which you then have to unwind while they hold a copy.
The invented line item
Ask for something slightly outside what you sell and an unconstrained model will write a reasonable-sounding service at a reasonable-sounding price. Neither exists. A catalog-backed generator cannot do this because it has nothing to draw from.
The stale template
Tools built on a template library quote last year's prices whenever nobody has updated the library. The prices are only right if a person keeps making them right.
The discount nobody saw
Speed without a rule means a rep can send 20% off in ninety seconds. The point of approval is catching the exception, not taxing every document.
Most AI document tools do one of these three. This does all of them.
Almost everything in this category bolted AI onto a product designed before it existed, so it speeds up one step: filling a template faster, or tidying a paragraph. DocuDeal was built the other way round. The AI is how the document gets made, how the signed copy gets understood, and how everything you have sent one client gets summarised in one place.
It writes every document
Proposal, quote, contract, NDA or statement of work, from the call transcript, the notes and the attachments you already have. No template built first, no tidying up before it goes in. Scope, assumptions, terms, the priced table, recipients with signing order and the signature fields, all in one pass.
It reads every signed one back
The moment a document completes, the terms come out as fields: parties, effective and end dates, renewal date, whether it auto-renews, notice period, value, governing law and each side's obligations. A signed agreement stops being a PDF nobody opens and becomes a row you can filter.
It summarises across them
Everything you have ever sent one client sits on one link, with a written status note across all of it: what is signed, what is waiting on whom, what happens next. Across the whole repository you can see what renews in January, what carries a notice period shorter than sixty days, and what you actually committed to on the deal a colleague closed last year.
One tool for every document, priced per workspace rather than per person from Pro. That combination is the wedge, and it is why the honest answer to "which of these is the AI-first one" is this one.
Straight answers.
What is an AI quote generator?
A tool that turns a description of a deal into a priced, sendable quote. The important distinction is where the numbers come from. A good one uses a model to understand the request and choose items from your price list, then calculates the figures in code. A bad one asks a language model to produce the total, which is fast and occasionally wrong in a way that costs money.
Can AI be trusted to price a quote?
To choose what goes on it, yes. To calculate it, no, and it should not be asked to. In DocuDeal the model selects catalog items and writes the language; unit prices, volume tiers, discounts, deposits and tax are arithmetic performed in code against rows you set up. That division is what makes the speed safe to use.
Do I need to build templates first?
No. Hand over a sentence, a set of notes or a call transcript and the quote comes back written and priced. You can save templates for the things that genuinely repeat, but nothing requires you to build a library before your first quote.
How do volume tiers and discounts work?
They live on the catalog item. Twenty-five seats crossing into a 25 to 99 band picks the band rate automatically, and because cost is stored beside price, the tool knows what a discount does to your margin rather than only to the total. Approval rules can fire on discount percentage, total value or document type before anything is sent.
Can the client change quantities themselves?
Yes, where you allow it. Optional lines and recipient-editable quantities recalculate in code on the page, so a client choosing three licences instead of two gets a correct total rather than a note asking you to re-issue.
What does it cost?
Free for 3 documents a month with no card. Starter is $49 a month, Pro is $149 with unlimited users, Business is $449. Quoting is not a separate module and seats stop being the meter from Pro.
What it does not do.
Stated plainly, because every one of these is something this page could be assumed to cover.
- It will not invent a price. If something is not in your catalog it is flagged to confirm, not filled in with a plausible figure.
- It is not CPQ for configurable manufacturing with dependency rules between components. It handles products, tiers, bundles, optional lines and recurring intervals.
- It does not quote from a competitor's price list or scrape market rates. The catalog is yours.
AI proposal generator
An AI proposal generator that starts from your call transcript and notes rather than a blank template, prices from your catalog, and tells you what to do when the client goes quiet.
AI document generation
Classic document assembly merges data into templates somebody maintains. AI document generation writes the document from what you already have. How both work, where each one fits, and what changes when there is no template.
AI contract generator
Generate a contract, NDA or SOW from a description of the deal, with the commercial terms computed from your catalog and the signed copy read back into fields. What it does, and plainly what it is not.