Quote automation that starts with your rules.
We encode your quoting rules — tiers, floors, discount authority, approval windows — against the data you already keep, so the system drafts the quote.
Official services partner of the platforms defining AI
NVIDIA
Anthropic
The rules live in someone’s head.
From sales floors we have sat with: a complex-product manufacturer with a permutation catalog and national contract-services sellers — not shopping for software, drowning between the inbound request and the number going out.
Quoting takes days
Hundreds of thousands of product permutations — shape, packaging, decoration — turn every quote into a multi-day research project before a number goes out.
What did this customer pay last year
Price history, margin trend, and account health take digging across systems, so the number that goes out depends on who did the digging.
Approval by email ping
Every deal needs three C-level approvers inside a 24–48h window, and today the chase runs on email pings and chat messages.
The pro forma gets rebuilt for every bid
Deal pro formas are built in Excel, downloaded, corrected, and re-circulated — by hand, every time, with the pricing schedules interpreted along the way.
The heuristics live in one head
Standard times, tier breaks, and when a discount is safe — the quoting judgment your best salesperson carries, consistent only while they are around.
A week for a quote is a line item, not a feeling.
What the manual way looks like at a seller whose quote rules live in inboxes and someone’s head. Your numbers will differ — the first quote desk we trace puts figures on yours before anything gets built.
From anonymized engagements — a complex-product manufacturer and national contract-services sellers
We encode your quoting rules.
No new system for your team to learn. Automating complex quoting starts with the rules your best estimator carries — encoded, they become the system.
- 01
Shadow one quote desk
We trace a week of quotes from request to sent price and find where the hours actually go — price lookup, approval chase, pro forma rebuild.
- 02
Encode the quoting rules end-to-end
Pricing tiers, cost-plus floors, discount authority, approval windows, the estimator’s heuristics — documented against the customer, product, and price data you already keep.
- 03
The system drafts every quote
Each incoming request is priced against your rules; anything that breaks one lands in an exception queue with the rule it broke.
The software gives you a blank rules engine. Your quote rules are the product.
A CPQ implementation is a months-long configuration project your team then maintains inside the vendor’s data model. The platform sells the engine; the consulting bill sells the configuration.
Your quote rules — the tier breaks, the floors, the approval thresholds your best estimator carries — are the product. We encode those; our AI reads each incoming request against them, and only the exceptions reach a person.
Led by Peter Enestrom.
Asked by sales directors and pricing leads.
The straight answers, before you book anything.
Quote automation is the production of a sales quote from an incoming request without a person assembling it by hand: the customer, the products, the pricing rules, and the terms come together into a draft that a person reviews. Sales quote automation applies the same idea inside a sales team — the request arrives, the system prices it against your rules, and the rep sends the result.
CPQ software gives you a rules engine and a data model your team configures and then maintains — typically a months-long implementation. We start from the rules instead: the pricing tiers, floors, discount authority, and approval windows your team already works by, encoded against the data you already keep. There is no new system of record to adopt, and the encoded rules are yours to keep.
Yes. The intake is usually unstructured — an email thread, a questionnaire, notes from a site walk — and reading it is the part AI handles well. Each request is read against your encoded rules, priced, and drafted; your team reviews the draft instead of building it. A questionnaire-to-quote flow is a normal starting shape.
It goes to an exception queue instead of to the customer. The quote is flagged with the rule it broke — a discount past the floor, a margin below threshold, an approval window that needs a signature — and a person decides. Nothing the rules would reject goes out unattended.
No. Reps keep working where they work today — the request comes in, the drafted quote comes back, and only exceptions ask for a decision. When the request is a formal RFP or RFQ rather than a quote, that is a different workflow, covered on our RFP-response page.
Start with one workflow.
Tell us where your team loses hours. We will come back with a straight answer on whether AI can help, what it would take, and what it would pay.