Trust the number before the forecast call
Your forecast rides on rep confidence and CRM fields that may not match what was said on the call. Semarize scores every sales conversation against your methodology and rolls it up by deal - so you can see which commits are qualified, which are exposed, and which are about to slip, without sitting in every call.
Kit
Deal Qualification Kit
Structured sales signals from a call transcript
Output
{
"meddicc_score": 74,
"stakeholder_mapped": ["VP Eng", "CFO", "Legal"],
"budget_confirmed": false,
"pricing_hesitation": true,
"next_step_confirmed": true
}
The problem
Deals live in conversations, not inside CRMs
The things that decide a deal - real next steps, committee dynamics, risk - are said on calls, not typed into fields. That leaves your forecast and your deal reviews running on partial data.
Your forecast is rep confidence in a spreadsheet
Commit calls run on how sure each rep sounds, not on signal from the actual conversations.
You can't tell which deals are really qualified
Methodology gets box-checked in the CRM. Whether the call covered the economic buyer or the decision criteria is invisible from your seat.
Single-threaded deals look healthy until they vanish
A deal carried by one friendly contact reads green right up until that contact goes quiet.
Risk reaches you after the deal has slipped
Pricing pushback and competitor threats are spoken weeks before they hit the CRM. By then the quarter is set.
The only way to really know is to listen
And no leader has time to sit in every conversation their team has.
For sales leaders
Inspect every deal, without joining the call
Each conversation runs through the same Sales Kit and rolls up by deal - so qualification, exposure, and slippage are visible across the whole pipeline, not buried in calls you will never have time to hear.
01 / Deal inspection
Know which deals in your commit are actually qualified
When you run the forecast call, you are taking each rep's word that the deal is real. Semarize scores every conversation against MEDDICC, BANT, or your own framework and rolls the result up by deal. You see which commits are genuinely qualified, which are missing an economic buyer or a decision criterion, and which are happy ears - before you bet the quarter on them.
Opportunity
Vantage Robotics - Platform
0
/ 100
02 / Pipeline exposure
Spot the single-threaded deals before they stall
A deal riding on one friendly contact looks healthy in the CRM, right up until that contact goes quiet. Semarize tracks who is actually engaged across the cycle - economic buyer, champion, blockers - and flags the opportunities that are single-threaded or missing a decision-maker. The exposure shows up while you can still do something about it, not in the loss review.
03 / Slippage signals
See what's about to slip before the forecast call
Pricing pushback, a competitor named in passing, a call that ends with no next step - the tells that a deal is sliding get said weeks before the number moves. Semarize surfaces them across your open pipeline and ranks the deals most likely to slip, so the forecast call opens with the at-risk list already in front of you.
Opportunity
Brightwave Health - Platform
0
deal risk / 100
How it works
How Semarize turns sales calls into deal intelligence
Connect the calls and transcripts you already capture. A Sales Kit of Bricks evaluates the signals you care about, attaches the evidence, and returns structured fields ready for your CRM, forecast, and coaching workflows.
- Step 1
Conversation captured
Sales calls, meeting transcripts, emails, and CRM notes are ingested.
- Step 2
Sales Kit runs
Bricks evaluate specific sales signals against your methodology and knowledge.
- Step 3
Signals extracted
Scores, flags, and extracted values are returned with confidence.
- Step 4
Evidence attached
Each signal carries the quote and span it was drawn from.
- Step 5
CRM and forecast updated
Typed fields feed CRM, forecasting, coaching, BI, and automation.
Example Bricks
The sales signals Semarize returns
Each Brick is a typed check that evaluates one sales signal and returns a structured value with confidence, reason, and evidence. Bundle them into Kits to score every conversation the same way.
Methodology scoring
MEDDICC adherence for the deal
Customer pain explicitly confirmed
Economic buyer named and engaged
Decision criteria captured on the call
Stakeholder mapping
Stakeholders identified with their roles
Internal champion driving the deal
Decision maker engaged in the conversation
Blocker or detractor surfaced
Deal risk
Pushback or hesitation after pricing
Competitor named, with context
Clear next action with owner and date
Procurement or legal delay detected
Overall deal risk level
Example output
Structured signals, not summaries
The Deal Qualification Kit returns the same schema every run: typed values, confidence, and evidence spans tied back to the call they came from.
Deal Qualification Kit returned
CRM-ready fields written straight to the opportunity
- MEDDICC score
- 74
- Champion
- VP Engineering
- Economic buyer
- Not confirmed
- Budget
- Not confirmed
- Competitor
- Rival Co
- Pricing hesitation
- Detected
- Next step
- Confirmed
- Forecast risk
- Medium
{
"run_id": "run_def456",
"source_call": "call_9f21",
"status": "succeeded",
"output": {
"bricks": {
"meddicc_score": {
"value": 74,
"type": "score",
"confidence": 0.90,
"reason": "Strong champion and metrics defined, paper process unclear",
"evidence": [
{ "quote": "Sarah is driving this internally", "span": [812, 844] }
]
},
"champion_identified": {
"value": "VP Engineering",
"type": "extracted",
"confidence": 0.88,
"evidence": [
{ "quote": "I will get this in front of the team", "span": [1290, 1330] }
]
},
"pricing_hesitation": {
"value": true,
"type": "boolean",
"confidence": 0.83,
"evidence": [
{ "quote": "that is higher than we expected", "span": [2104, 2139] }
]
},
"forecast_risk": {
"value": "medium",
"type": "category",
"confidence": 0.79
}
}
}
}The difference
Why a summary won't survive a forecast call
A summary is written for someone to read after the fact. To trust a forecast you need signal you can sort, rank, and compare across every deal.
Call summaries
Structured sales signals
FAQ
Sales conversation intelligence, answered
How methodology scoring, stakeholder mapping, and deal-risk detection work on real sales calls.
Keep exploring
Where sales signals go next
The same structured outputs feed adjacent teams and the product layer underneath.
CRM enrichment, forecasting, and pipeline hygiene owned by RevOps.
Coaching and methodology adoption measured across every rep.
Define the typed signals Semarize evaluates on each call.
Bundle Bricks into reusable sales workflows.
Implement Semarize in your own stack and pipelines.
See how Bricks, Kits, and outputs fit together.
Get started
Walk into the forecast call already knowing
See which deals are qualified, which are exposed, and which are about to slip - from every conversation your team has, without sitting in them.
No card required. Start testing in minutes.