Commercial Operations · Live
Approve the deal in seconds. Send the quote knowing it's right.
For the people approving deals and the people pricing them. The first Objeqt module turns your quote history and your rules into recommendations that come with the reasoning attached.
30-min walkthrough · We'll run your first file with you
Most deals approve on memory and habit.
A deal desk lead reviews dozens of quotes a week — each from a different region, customer, account team. The reasoning lives in heads, spreadsheets, and last quarter's CRM export. Slow. Inconsistent. No paper trail.
When finance asks why the discount was approved at 14% and not 11%, there's no defensible answer. The deal moves anyway. The next one too.
From quote history to a verdict, in three steps.
Bring your history
Drop in past deals as an Excel file — price, cost, product, customer, won or lost.
Match the quote
We find similar past deals by product, region, quantity, and won/lost outcome.
Get the verdict
A clear read, a suggested price range, and the deals that back it up.
One engine. Three surfaces.
Justification Builder
For the deal desk lead approving the deal — every approval comes with a defensible reasoning trail.
Quote Margin Check
For the salesperson in flow, setting the price — too cheap, on target, or too high, before it's sent.
Scenarios
Ask a what-if and see it — a customer leaving, costs moving, a big order arriving — with the margin walk and who's affected.
Same data. Same logic. All auditable.
Surface 01 · Justification Builder
A defensible reasoning trail for every approval.
When a quote lands for approval, Objeqt assembles the reasoning automatically: strategic context, pricing precedent, volume basis, margin implication. Each section grounded in your data, with the source shown.
Every approve, override, and reject teaches the system. The decision becomes signal for the next similar deal.
Now live · Scenarios
Ask a what-if. See where it lands.
Pricing isn't the only commercial decision that moves margin. Scenarios lets you model a change before it happens — a customer leaving, an input cost moving, a big order arriving — and see the impact on your book, who's affected, and what to do about it. Grounded in your own deal history, with every number showing its source.
What if a customer leaves?
The revenue at risk over the next 12 months, the products exposed, and the customers worth pushing to replace the volume.
What if a key input cost moves?
The margin walk across your book — what it would have cost over the last year and what it projects forward — and which deals to reprice.
What if a big order arrives?
Which of your sites can fulfil it, the margin picture at that volume, and a feasible counter-offer.
Frame the question, set the case, and the engine walks your data. Move a slider — cost up 12%, down 8% — and it re-runs instantly. See the blast radius of every customer and SKU affected. Get repricing recommendations backed by precedent. When the data can't support a number, the scenario says so — no invented figures.
Same ontology. Same provenance. A new verb — simulate.
The pilot
Five days to live. Thirty days to measure.
Upload your quote history. Configure the ontology.
Run your first quotes through the engine. Calibrate against your team's reasoning.
Go live with the deal desk and a sales pilot group.
Measure approval time, margin variance, override patterns.
By 30 days you know whether Objeqt earns its place.
See Commercial Operations on your data.
A 30-minute walkthrough, your quote history, your decisions. By the end of week one, you'll know whether Objeqt holds up against the deals you actually have to price.