Semarize
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Use caseSales

Intelligence for every sales conversation

From a first discovery call to a multi-stakeholder enterprise deal, every conversation carries signal. Semarize scores each one against your methodology and returns structured fields for forecasting, deal risk, and pipeline - on every run.

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Methodology scoringStakeholder & champion mappingForecast & deal-risk signals
SSaleskit run

Kit

Deal Qualification Kit

meddicc_scorescore
stakeholder_mappedstring_list
budget_confirmedboolean
competitor_mentionedextracted
pricing_hesitationboolean

Output

{

"meddicc_score": 74,

"stakeholder_mapped": ["VP Eng", "CFO", "Legal"],

"budget_confirmed": false

}

The problem

The deal lives in the conversation,
not the CRM

Pipeline decisions depend on accurate signals. But the things that move deals - committee dynamics, risk, real next steps - are said on calls, not typed into fields.

Buying committees are opaque

Enterprise deals involve 6–10+ stakeholders. Tracking who has been engaged, their role, and their sentiment across calls requires structured data, not notes.

Forecasts are based on opinion

Forecast calls rely on rep confidence and manager gut feel, not structured signals from the actual conversations.

Methodology adoption is unmeasured

MEDDICC, BANT, or Challenger - you invest in methodology but can't measure whether reps apply it on real calls.

Deal risk surfaces too late

Pricing objections, competitor threats, and procurement delays show up in calls weeks before they reach the CRM. By then, intervention is too late.

Why existing tools fail

Existing tools describe calls,
not the deal

Conversation tools and CRM reports describe activity. They don't return structured, queryable signals about deal health across a buying committee.

Conversation intelligence platforms

Produce call summaries and highlight reels for humans to read. You can't query methodology scores or stakeholder coverage across a multi-call deal.

CRM reports

Show what reps typed into fields, not what was actually said. Budget, stakeholders, and risk depend on manual, inconsistent data entry.

Forecasting tools

Model pipeline from CRM activity. If the underlying conversation signals never get captured, commit accuracy stays low.

The Semarize approach

Semarize scores
every deal, every call

Define Bricks for the signals that matter, bundle them into a Kit, and run every sales conversation through the same evaluation - automatically.

Methodology scoring

Score MEDDICC, BANT, or your custom framework per call and per deal. See exactly which criteria were covered and which were missed.

Stakeholder & champion mapping

Extract who is involved, their role, and who is championing the deal across every conversation in the cycle.

Forecast & deal-risk signals

Detect pricing hesitation, competitor mentions, procurement blockers, and missing next steps. Flag at-risk deals before they slip.

CRM-ready fields

Boolean flags, numeric scores, and extracted values written straight to opportunity records - not narrative summaries.

Bricks & Kits

Example Bricks for
sales

These Bricks evaluate the specific dimensions that matter for sales teams & leaders. Bundle them into Kits to create reusable evaluation frameworks.

meddicc_score
score 0–100

MEDDICC methodology adherence for the deal

→ 74
stakeholder_mapped
string_list

Key stakeholders identified with roles

→ ["VP Eng", "CFO", "Legal"]
budget_confirmed
boolean

Explicit budget confirmation or commitment mentioned

→ false
competitor_mentioned
extracted

Competitor names and context identified

→ "Gusto"
pricing_hesitation
boolean

Pushback or hesitation after pricing discussion

→ true
next_step_confirmed
boolean

Clear next action with owner and date agreed

→ true

Deal Qualification Kit

kit

Qualify every opportunity against your methodology.

meddicc_scorescore
stakeholder_mappedstring_list
champion_identifiedstring_list
budget_confirmedboolean
next_step_confirmedboolean

Forecast Risk Kit

kit

Surface deal risk signals from every conversation.

budget_confirmedboolean
pricing_hesitationboolean
competitor_mentionedextracted
next_step_confirmedboolean

Output

Structured signals,
not summaries

Every evaluation returns deterministic JSON with typed values, reasons, and evidence spans. Same schema every time.

Deal qualification evaluation
{
  "run_id": "run_def456",
  "status": "succeeded",
  "output": {
    "bricks": {
      "meddicc_score": {
        "value": 74,
        "confidence": 0.90,
        "reason": "Strong champion, metrics defined, but paper process unclear",
        "evidence": ["...Sarah is driving this internally...", "...targeting 40% faster onboarding..."]
      },
      "stakeholder_mapped": {
        "value": ["VP Eng", "CFO", "Legal"],
        "confidence": 0.87,
        "reason": "Three stakeholders identified across conversations",
        "evidence": ["...need to loop in our CFO...", "...legal will review the MSA..."]
      },
      "budget_confirmed": {
        "value": false,
        "confidence": 0.93,
        "reason": "Budget not explicitly confirmed",
        "evidence": ["...we don't have budget until Q3..."]
      }
    }
  }
}

Close more of
the right deals.

Score every conversation against your methodology. Map stakeholders, surface risk, and forecast with real signals.

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