Sales and pricing
Automatic Quoting
Quotes built from what your jobs actually cost and how your quotes actually landed, so each one protects margin. Estimators quote faster, and customers can get a quote and place a deposit on your website.
The problem
A good quote depends on more than a person can weigh at once: the job's details, materials and labor, the customer, the region, and how similar jobs really turned out. So quotes vary by who writes them and how busy they are, some jobs are won at a loss, and others are lost on price. A general-purpose chat model does not help here, because it has never seen your costs or your outcomes.
Who owns it
The head of sales or estimating, with finance as co-owner of margin floors and approval thresholds. Estimators handle the quotes that fall outside the bounds.
What it learns from
- Past quotes and whether each was won or lost
- The delivered cost and margin of each job
- Job and line-item attributes
- Materials and labor rates
- Customer and region
How it works
Predict, decide, act, measure
The same four steps in every solution, in this order, each one visible to the team that owns it.
- 01
Predicts cost, its uncertainty, and the chance to win
Models trained on your delivered jobs predict what a job will cost, how uncertain that estimate is, and how likely the customer is to accept at a given price. Their accuracy is measured on jobs they never saw, and the drivers behind each estimate are shown: what actually moves cost, margin, and win rate.
- 02
Decides the quote through a pricing policy
Margin floors, a risk buffer that grows with the uncertainty of the cost estimate, and discount limits set the quote. A quote outside the bounds, or above the value threshold your team sets, goes to an approver instead of out the door.
- 03
Acts in the CRM, the quoting tool, or on your website
For your own teams, the quote and its reasons land in the CRM or quoting tool your sales and estimating teams already use. For self-serve, the quote appears in your website's quote flow, where the customer can place a deposit. Anything out of bounds is routed to an estimator.
- 04
Measures against your current quoting process
A champion and challenger comparison, or a holdout that keeps the current process, measures win rate and quote turnaround. As jobs are delivered, quoted cost and margin are checked against what each job actually cost and earned.
What it moves
The business levers
Win rate
Prices set with the chance to win in view, rather than by habit.
Speed to quote
Consistent quotes in less time, so the customer hears back while still deciding.
Self-serve deposits
Customers who can quote themselves on your website can commit on the spot.
Underpriced jobs avoided
Margin floors and an uncertainty buffer keep the company from winning work at a loss.
Proof
How the return is proven
The return is the incremental margin and win rate of policy-set quotes over the current process, net of jobs that came in over cost, stated against the return model agreed up front. Quoted against actual cost on every delivered job is the standing check that the quotes are defensible.
What you see: the ROI readout
Every solution produces the same readout, assembled from the system's own records rather than built by hand.
Correctness
The checks the pipeline passed on your own data: leakage, point-in-time, and entity resolution.
Incrementality
The incremental effect against the holdout or equivalent design, with its confidence interval.
Return
The measured return against the investment, set beside the return model agreed before work started.
Guardrails
Complaints, cost, margin, fairness, and contact limits, each shown against its bounds.
Audit extract
Every score, action, and outcome, with the model and policy versions behind it.
Governance
What is governed
Access, approvals, and the audit trail are part of the solution, not a review step added at the end.
Identity-scoped access
Quotes, costs, and margins are visible by role through your single sign-on.
Approval gates
Quotes outside the bounds or above the value threshold, and any discount beyond its limit, need a named approver.
Audit trail
Every quote is logged with the model and policy versions that produced it, and with the outcome once the job is won, lost, or delivered.
Explainable drivers
Every quote carries the drivers behind it, so an estimator or approver can see why it came out where it did.
Why it holds up
Trained on your data, framed by the outcome
This solution trains models on your own data, checks every stage from data to decision, and is measured against the outcome it was built for. Because its predictive power is measured, it also shows the drivers behind the metric, so your team can fix causes as well as act on scores.
Why solutions hold upStart with one decision
Bring the problem and the systems your team works in. We scope the first solution with you, agree how its return will be measured, and run it in production with your people.