Know what you know about the customer. And what you don't.
Every number in a valueIQ value model traces back to cited evidence, or is clearly marked as an estimate to verify. No AI hallucinations dressed up as facts.
Fictional example. Every figure shows its evidence, so the gaps are visible before the first meeting.
A confident number with no source is a hallucination waiting to be found.
General AI tools invent plausible numbers.
Ask a general-purpose model for an ROI figure and it will give you one, stated with confidence and with nothing behind it. The first time the economic buyer asks where it came from, the deal loses trust.
Sellers cannot tell what is solid from what is assumed.
When every number looks equally certain, nobody knows which ones to check. Discovery starts from a blank slate, and the risky assumptions surface in the finance review.
A business case is only as strong as its weakest unsourced figure.
One number the buyer cannot verify is enough to put the whole case in doubt.
How every number earns its place.
Cited sources on every estimate.
Market estimates are built from research, and each one lists its sources with links. You can open the evidence behind any figure instead of taking it on trust.
Reasoning and confidence, shown.
Each estimate shows the reasoning that ties its sources to the chosen value and range, and a confidence score. Where the evidence is thin, valueIQ says so with a lower score instead of filling the gap.
Provenance on every variable.
Every number in a business case shows who stands behind it: a market default, a figure the seller set, or a value the customer confirmed. The full history of changes and confirmations is kept.
AI workflows you can audit.
The AI workflows that build each model run as recorded, step-by-step processes. The trail behind a number is visible in the product and can be surfaced for a customer on request.
Discovery becomes verification, not a blank slate.
Because every number carries its evidence and its confidence, a seller walks into the first meeting knowing exactly what is trustworthy and what still needs the customer.
- 01
Start from evidence
The value model and the customer model arrive with sourced estimates for the account and the product fit.
- 02
See the gaps
Sort by confidence to find the figures the model is least sure of. Those become your discovery questions.
- 03
Verify together
Walk the customer through the numbers. They correct what is wrong and confirm what is right, in a shared business case.
- 04
Present what the customer stands behind
The case that reaches the economic buyer rests on figures the customer has confirmed, with sources for the rest.
The Co-Session Discovery Guide: discovery you run with the customer.
Uncertain figures, shown to the customer.
The Co-Session Discovery Guide is a live, shared session the seller runs with the customer on screen. It surfaces the customer variables the model is least sure of, with the evidence behind each, so the customer can confirm their own numbers.
Open questions about pains and value delivery.
The guide also lays out what is still uncertain about the customer's pains and how value will actually reach them, as questions answered together during the session.
Trust built in the open.
Nothing is hidden behind a polished number. The customer sees what is sourced, what is assumed and what they confirmed, and every answer flows back into the deal for the business case that follows.
Already building business cases in a chat assistant? Ground it first.
Connect valueIQ's MCP Server to your assistant, and the business case it drafts rests on the same sourced value model instead of the model's best guess.
- 01
Connect valueIQ
Connect the valueIQ MCP Server to Claude, ChatGPT or Cursor. Set it up in five minutes.
- 02
Build the value model
valueIQ researches the account and the product fit, then writes a value model with cited, risk-adjusted market estimates.
- 03
Generate the business case
Ask your assistant for the business case. It draws on the sourced value model through the MCP Server, so every number traces back to evidence.
- 04
Walk in knowing the gaps
Confidence scores show what is solid and what still needs the customer, so discovery stays a verification exercise, not a blank slate.
Guesswork versus grounded
Bring evidence to your next deal.
Build your first value model free and open the sources behind every number. No credit card is needed.
Frequently asked questions
Every market estimate is built from research and lists the sources it came from, with the reasoning that connects them to the chosen value and a confidence score. Numbers the model cannot support with evidence are shown with low confidence, so they read as estimates to verify, not as facts.
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