Revenue Intelligence Platform for B2B SaaS
Go beyond dashboards. DealARR uses AI to surface risks, predict revenue trajectories, generate board-ready reports, and tell you what to do next.
AI-Powered Revenue Intelligence
DealARR's intelligence layer transforms your deal book data into predictions, recommendations, and automated reports that drive better decisions.
Churn Risk Scoring
AI identifies at-risk customers with probability scores, contributing factors, and recommended intervention strategies.
Revenue Forecasting
12-month ARR/MRR projections with confidence intervals, scenario modeling, and per-rep predictions.
Industry Benchmarking
Compare 20+ metrics against P25/P50/P75/P90 percentiles for your industry and stage.
AI Board Reports
Auto-generated board reports with dual narratives: a balanced shareholder summary and a direct internal briefing.
ICP Analysis
AI identifies your Ideal Customer Profile based on win patterns, retention rates, and expansion revenue.
Revenue Chatbot
Ask questions about your data in natural language and get instant, context-aware answers with source references.
How Revenue Intelligence Works in DealARR
Your data flows in
Deals, invoices, and metrics are captured from your deal book, CRM imports, and accounting integrations.
AI analyzes patterns
Machine learning models identify trends, risks, and opportunities across your entire revenue dataset.
Insights are surfaced
Churn risk alerts, forecast updates, benchmark comparisons, and recommended actions appear in your dashboards and reports.
Reports generate automatically
Board reports, investor decks, and performance reviews are created with AI narratives you can edit and share.
Revenue Intelligence FAQ
Revenue intelligence uses AI and data analytics to transform raw revenue data into actionable insights. Instead of just showing what happened, it tells you what's likely to happen, what's at risk, and what to do about it.
DealARR uses AI (Claude and OpenAI) for churn risk scoring, ARR/MRR forecasting, industry benchmarking, ICP analysis, board report narrative generation, investor deck creation, commission policy extraction from PDFs, and a conversational chatbot that answers questions about your data.
DealARR's AI models are trained on your actual deal book data, not generic datasets. Forecasting uses linear regression with confidence intervals. All AI outputs include context about data quality and should be reviewed by your team before acting on them.