Sales & Revenue Intelligence
Probabilistic revenue forecasting, not pipeline fiction
Score deal quality, validate close dates, build bottoms-up probabilistic forecasts, and protect margins with discount guardrails - replacing CRM gut-feel with structured decision science.
Challenges We Solve
Common pain points that structured decision models eliminate.
Pipeline Opacity
Pipeline data tells you what reps entered, not what's real. Score deal quality, validate close dates against historical patterns, and expose pipeline risk objectively.
Discount Leakage
Every deal gets a 'special' discount. Model the cumulative revenue impact of discount patterns, enforce guardrails, and protect margins at scale.
Forecast Inaccuracy
Quarterly forecasts swing wildly from commit to close. Build probabilistic forecasts from pipeline stage, deal velocity, and historical conversion data.
Churn Blind Spots
Renewals slip through the cracks until it's too late. Score renewal risk continuously and trigger intervention playbooks before customers defect.
Agent Orchestration in Action
Autonomous AI agents collaborate to detect, diagnose, and resolve revenue risks with human-in-the-loop guardrails at every step.
Detects 3 committed deals past close date from CRM sync
Monitors Salesforce/HubSpot webhooks after every sync. Automatically flags deals in Commit/Upside that exceed close date by >7 days without stage progression.
Re-scores deal quality and win propensity for slipped deals
Runs deal_quality_scoring and win_propensity models. 2 of 3 deals downgraded from 75%+ to <40% win probability based on velocity stall, missing champion activity, and competitor mentions in Gong calls.
Validates timeline realism and checks margin impact
Runs close_date_realism against historical conversion patterns. Projects realistic close: Q+1 for 2 deals, likely lost for 1. Runs win_rate_discount_curve to check if discount escalation is eroding margins.
2 of 3 agents agree: forecast needs $4.2M downward revision
Multi-agent consensus confirms pipeline at risk. Combined shortfall of $4.2M against quarterly commit. Recommends coverage ratio increase and pipeline generation sprint.
Generates pipeline health briefing with recovery plan
Synthesizes deal-level risk scores, realistic close timeline, and coverage gap analysis into a prioritized CRO briefing. Recommends pulling 2 acceleration deals forward and launching outbound campaign for pipeline gap.
Built-in Guardrails
Monday Morning Intelligence Briefing
This is what your CRO sees every Monday at 6 AM, automatically generated from 10+ model outputs, zero analyst hours required.
WORKFORCE INTELLIGENCE BRIEFING
Generated: Mon May 19, 2026 6:00 AM ET · $48M ARR, 340 active opportunities
3 committed deals ($4.2M combined) slipped past close date. Win probability downgraded to <40% for 2 of 3. Q2 commit gap now $4.2M.
- Deal velocity stalled: avg 47 days in current stage (benchmark: 22 days)
- Champion contact frequency dropped 80% in last 3 weeks
- Competitor mentioned in 2 of 3 latest Gong recordings
Pipeline coverage ratio dropped to 1.8x (target: 3.0x). Immediate pipeline generation needed to close $4.2M gap.
Average discount increased from 18% to 24% over 2 quarters. Cumulative margin impact: $680K annualized.
- 3 reps consistently discounting >30% (team avg 18%)
- Competitive pressure in cybersecurity vertical driving deeper discounts
- No discount approval workflow enforced below $100K deal size
win_rate_discount_curve shows diminishing returns beyond 20% discount. Recommend guardrail at 22% with VP approval for exceptions.
8 of 42 Q3 renewals scored HIGH RISK (>0.60). Combined ARR at risk: $1.8M. Average health score: 42/100.
- Product usage dropped >40% for 5 accounts in last 90 days
- NPS detractor responses from 3 accounts in latest survey
- 2 accounts have active support escalations unresolved >30 days
renewal_risk_score model run #R-5044 attached with account-level intervention playbooks.
Discovery-to-Proposal conversion dropped from 62% to 48% in the last 30 days. 14 deals stalled in Discovery.
- New qualification criteria introduced last month may be too restrictive
- 2 new reps in ramp period contributing to lower conversion
stage_conversion model recommends reviewing qualification criteria and pairing new reps with senior mentors.
| Metric | This Week | Prior Week | Trend |
|---|---|---|---|
| Pipeline Value | $28.4M | $31.2M | ↓ ⚠ |
| Coverage Ratio | 1.8x | 2.4x | ↓ ⚠ |
| Win Rate (QTD) | 24% | 28% | ↓ ⚠ |
| Avg Deal Size | $142K | $138K | ↑ |
| Avg Discount | 24% | 22% | ↑ ⚠ |
| Forecast Accuracy | 71% | 78% | ↓ ⚠ |
| Gross Retention | 91% | 93% | ↓ ⚠ |
Use Cases
How teams use DecisionLedger to make better decisions.
Runs the deal quality scoring model across the entire pipeline weekly, flagging deals with inflated close dates, missing champion signals, or stalled velocity - replacing forecast calls with data.
Forecast accuracy improved from 60% to 88% with probabilistic scoring
Uses the discount curve model to analyze cumulative margin impact of discount patterns by segment, rep, and deal size - setting guardrails that protect margins without blocking deals.
Recovered 3.2% margin by enforcing data-driven discount guardrails
Deploys the renewal risk model to score every customer's churn probability 90 days before renewal, triggering intervention playbooks for high-risk accounts.
Gross retention improved from 88% to 94% with proactive intervention
From 2-Week Cycle to Continuous Forecast
See how agent orchestration compresses an 8-week manual process into same-day resolution.
Manual Process
2 weeks
6 people, 80+ hours of pipeline reviews
With DecisionLedger
Always current
0 manual pipeline reviews, fully audited
Measurable Impact
Based on platform benchmarks across early adopters.
Forecast Accuracy
+/-25% variance
+/-8% accuracy
Discount Control
Ad-hoc approvals
Model-backed guardrails
Renewal Risk
Discovered at renewal
90-day early warning
Pipeline Hygiene
Rep self-reported stages
Velocity-validated scoring
Compliance on Autopilot
Every HR decision model includes built-in regulatory compliance checks. Always audit-ready, never scrambling before a review.
Revenue Recognition
ASC 606 compliant deal scoring with multi-element arrangement analysis and variable consideration estimates
Discount Authority Matrix
Automated discount approval workflows enforcing role-based limits with escalation paths and margin floor protection
Channel Conflict Policy
Partner deal registration validation, territory overlap detection, and channel margin compliance monitoring
Pricing Governance
List price enforcement, competitive response documentation, and discount pattern analysis for anti-trust compliance
Forecast Certification
Quarterly forecast sign-off workflow with assumption documentation, bias tracking, and audit trail
Immutable Audit Trail
Every model run archived to S3 Object Lock WORM storage for revenue audit, SOX compliance, and deal review
The HR Automation Stack
Six end-to-end automated workflows that chain multiple decision models together. Each pipeline runs autonomously with governance gates.
Pipeline Hygiene
Daily CRM sync
Every deal rescored daily with validated close dates and quality flags
Forecast Build
Weekly + quarterly
Bottoms-up probabilistic forecast with bias adjustment and coverage analysis
Renewal Risk
Continuous
Account-level risk scores with intervention playbooks and expansion signals
Discount Approval
Deal event
Data-backed discount recommendations with margin impact analysis and approval routing
Built for Every People Leader
Whether you lead the function or the analytics, DecisionLedger delivers the outputs your role demands.
For the CRO
- Weekly intelligence briefings synthesizing pipeline health, forecast risk, and margin trends into one page
- Probabilistic revenue forecasting with P10/P50/P90 bands replacing gut-feel commit calls
- Discount erosion monitoring with pattern analysis across segments, reps, and deal sizes
- Autonomous pipeline scoring that flags slipping deals before they miss quarter
For the VP Sales
- Deal-level quality scores replacing subjective manager assessments in pipeline reviews
- Close date validation against historical conversion patterns by segment and deal size
- Stage conversion analysis identifying where deals stall and what interventions accelerate them
- Rep performance insights correlating activity patterns with win rates and deal velocity
For the RevOps Director
- Automated pipeline hygiene scoring eliminating manual deal review cycles
- Forecast bias tracking and correction improving accuracy quarter over quarter
- Pricing governance enforcement with automated discount approval workflows
- Coverage ratio monitoring with pipeline generation triggers when gaps emerge
For the Customer Success VP
- Renewal risk scoring 90 days before renewal with account-level intervention playbooks
- Product usage decay detection correlating engagement drops with churn probability
- Expansion propensity models identifying upsell-ready accounts based on usage patterns
- Health score trending across the customer base with segment-level benchmarks
Connects With
Part of 150+ native integrations across CRM, marketing, finance, HR, ecommerce, and analytics
Salesforce
HubSpot
Pipedrive
Zoho CRM
Dynamics 365
Outreach
Salesloft
Apollo.io
Close
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Attio
ZendeskSalesforceHubSpotPipedriveZoho CRMDynamics 365OutreachSalesloftApollo.ioClosemonday.comAttioZendeskFeatured Models
Pre-built decision models ready to run with your data.
Close Date Realism
Compares stated close dates against historical stage-velocity patterns to flag unrealistic timelines. Outputs expected close date, slip probability, and days of bias per rep and stage.
Deal Quality Scoring
Multi-signal deal quality score combining ICP fit, intent signals, engagement depth, mutual plan indicators, and stakeholder mapping. Outputs composite score with driver decomposition using weighted MCDA scoring.
Pipeline Sla Forecaster
Predicts the likelihood of delayed or failed refreshes based on job history, dependencies, and runtime patterns. Recommends preemptive actions.
Renewal Risk Score
Assesses likelihood of churn by cohort, segment, and account health signals. Combines usage trends, support ticket patterns, stakeholder changes, and contract terms into a weighted renewal risk score with per-account recommendations.
Revenue Probability Model
Revenue Probability Model -- Monte Carlo simulation engine that models SaaS revenue trajectories. Takes go-to-market assumptions (ACV, close rate, pipeline, churn, sales cycle, ramp time) and runs 10,000 stochastic simulations to produce probability distributions for hitting revenue targets ($1M, $5M, $10M, $20M ARR). Outputs confidence intervals, time-to-target distributions, and sensitivity analysis on which levers move the needle most.
Stage Conversion
Calculates stage-to-stage conversion probabilities segmented by rep, source, segment, and deal size. Identifies where pipeline leaks occur and which segments convert best using Bayesian probability estimation.
Win Propensity
Probability of win given deal attributes including stage, source, segment, rep, deal size, engagement, and competitive presence. Uses logistic regression or ML classification with SHAP-based driver explanations. Falls back to heuristic scoring when training data is unavailable.
Win Rate Discount Curve
Maps the relationship between discount depth and win rate to identify diminishing returns and optimal discount guardrails by segment, deal size, and competitive situation.
How It Works
Three steps to structured, auditable decisions.
Score & Qualify Pipeline
Automatically score every deal on quality, win propensity, and close date realism. Surface the pipeline that actually matters.
Forecast & Protect
Build bottoms-up probabilistic revenue forecasts, detect discount patterns, and model pricing scenarios across segments.
Retain & Expand
Score renewal risk, identify expansion opportunities, and track customer health signals to protect and grow recurring revenue.
Your CRO commits a number every quarter based on what reps say they'll close. How many times has that number been right?
CRM pipeline reports
Opportunity stages that reflect rep optimism, not statistical close probability
Clari / BoostUp forecasting
AI-signal tools that predict revenue but can't run risk models or discount analysis
Spreadsheet discount approvals
Ad-hoc margin erosion with no pattern analysis or guardrail enforcement
Manual churn tracking
Renewal risk discovered at renewal time instead of 90 days in advance