Make Smarter Decisions with
AI-Powered Forecasting
Gut feelings and spreadsheet models got you this far. To go further, you need AI that sees patterns in your data humans can't — predicting demand, pricing risk, forecasting revenue, and recommending actions with quantified confidence levels.
Revenue Forecast Accuracy
Demand Prediction
Risk Assessment
Scenario Coverage
Where Decision Intelligence Changes Outcomes
Real forecasting systems making real predictions — tested against actual results, not backtests.
Revenue Forecasting
A multi-variable model that predicts quarterly revenue within 4% accuracy by incorporating pipeline data, market signals, seasonality, and deal velocity patterns.
SaaS & Enterprise SalesLoan Default Prediction
Forecasts which loans in the portfolio are likely to default in the next 90 days — enabling proactive outreach that reduced actual defaults by 22%.
FinTech & LendingDemand & Inventory Planning
Predicts SKU-level demand 12 weeks ahead, accounting for promotions, weather, and competitor pricing — reducing overstock by 28% and stockouts by 41%.
Retail & CPGEnergy Load Forecasting
Predicts electricity demand at 15-minute intervals for grid balancing. Accuracy within 2.1% enables smarter energy purchasing and storage decisions.
Energy & UtilitiesPatient Volume Forecasting
Predicts ER admissions and bed occupancy 72 hours ahead, enabling proactive staffing adjustments that reduced overtime costs by $1.2M annually.
HealthcareDecision Intelligence Platform Capabilities
From raw data to confident decisions — a complete stack for prediction, simulation, and recommendation.
Multi-Horizon Forecasting
Short-term (days), medium-term (weeks), and long-term (quarters) forecasts with confidence intervals — different models optimized for each time horizon.
Scenario Simulation
Run what-if analyses across hundreds of scenarios. "What if raw material costs rise 15%?" "What if we lose our second-largest client?" Get quantified impact assessments.
Causal Analysis
Go beyond correlation. Our models identify the drivers behind trends — which variables actually cause changes and by how much.
Prescriptive Recommendations
Not just "what will happen" but "what should you do." The system recommends actions with expected outcomes ranked by probability and impact.
Real-Time Signal Integration
Incorporate live data feeds — market prices, weather, social sentiment, web traffic — into predictions that update as conditions change.
Automated Reporting
Scheduled forecast reports delivered to stakeholders with variance analysis, confidence levels, and plain-language explanations of key drivers.
How We Build Your Forecasting System
Decision Audit
We map the key decisions your org makes — what data informs them, how accurate current forecasts are, and what a better prediction is worth in dollars.
Data Pipeline Design
We connect your data sources, clean and transform the data, engineer features, and build the data infrastructure that feeds the forecasting models.
Model Development & Testing
We train multiple model architectures, evaluate against historical data, and select the approach that delivers the best accuracy on your specific forecasting problem.
Dashboard & Integration
Forecasts are delivered through interactive dashboards, API endpoints, or directly into your planning tools — wherever your decision-makers work.
Accuracy Monitoring
Continuous comparison of predictions vs. actuals with automated alerts when accuracy drifts — plus quarterly model refresh cycles.
Spreadsheet Forecasts Cost You More Than You Think.
Get a free accuracy assessment — send us your last 12 months of forecasts vs. actuals and we'll show you the gap AI can close.
Book Free ConsultationDecisions backed by data, not hunches.
Decision intelligence replaces the intuition-based planning that works until it doesn't. When markets shift, supply chains break, or customer behavior changes, AI-powered forecasting adapts — spreadsheet models collapse.
Trustworthy Forecasts for High-Stakes Decisions
When forecasts drive investment decisions, staffing plans, and inventory purchases, accuracy and explainability are critical.
Why Teams Choose Us for Decision Intelligence
We've built forecasting systems that CFOs, COOs, and supply chain leads actually rely on for real decisions.
What Do You Need to Predict Better?
Tell us about the decisions you're making with imperfect forecasts — we'll respond with an approach and accuracy improvement estimate.
Case Study
B2B SaaS Platform Improves Revenue Forecasting Accuracy from 72% to 94%
A B2B FinTech SaaS company with $45M ARR was consistently missing quarterly revenue forecasts by 15-28%. The CFO couldn't give the board reliable guidance, and budgeting decisions were based on numbers everyone knew were wrong.
The Problem
Manual forecasting based on pipeline stage and rep estimates was consistently inaccurate, undermining strategic planning and board confidence.
Our Approach: We built a multi-signal forecasting model that incorporates CRM pipeline data, historical deal velocity, product usage patterns, payment history, macroeconomic indicators, and seasonality. The model weights each signal based on its predictive power — deprioritizing rep estimates (low accuracy) and upweighting usage patterns and payment behavior (high accuracy). Forecasts are generated weekly with 30/60/90-day horizons and confidence intervals. A dashboard shows the CFO exactly which deals are driving the forecast and which factors are creating uncertainty.
Frequently Asked Questions
BI tools do trend extrapolation — they extend the line. Our models incorporate dozens of variables, identify non-linear patterns, and weight signals by predictive power. The difference shows up in accuracy: typically 20-40% improvement over simple trend-based forecasts.
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