Can AI help with business forecasting?business forecasting
IRPR builds custom AI forecasting models that turn your historical data into 12-month revenue predictions. Ship a production-ready forecasting dashboard in 10 weeks, fixed price.
IRPR builds custom AI forecasting engines that analyze your historical sales, inventory, and financial data to predict future outcomes. We use Python, TensorFlow, and time-series models like Prophet and ARIMA to deliver 90%+ forecast accuracy.
A full-stack forecasting dashboard ships in 10-12 weeks, with a fixed price between $60K and $150K. The stack includes a React frontend, a Python API, and a PostgreSQL database, all deployed on AWS with SOC 2 compliance.
CFOs hire us to automate quarterly revenue forecasts. Supply chain directors need demand forecasting for inventory optimization. SaaS founders want churn prediction and MRR projections. Retail operators use us for store-level sales forecasting.
Types of software we ship.
Revenue Forecasting Dashboard
A real-time dashboard that ingests QuickBooks data and outputs 12-month revenue projections using XGBoost regression.
Demand Forecasting Engine
Predicts SKU-level demand by analyzing POS data and seasonal trends, integrating with Shopify and NetSuite.
Cash Flow Prediction Tool
Forecasts 90-day cash positions by modeling accounts payable and receivable, connected to Stripe and Plaid.
Inventory Optimization Model
Reduces stockouts by 40% using time-series forecasting on historical sales data, synced with SAP or Oracle.
Churn Prediction System
Identifies at-risk customers with 85% accuracy using logistic regression on Mixpanel and Intercom data.
Sales Pipeline Forecaster
Projects deal closure probability by scoring CRM leads with a random forest model, integrated with Salesforce.
Workforce Demand Planner
Predicts staffing needs by analyzing project pipeline and historical utilization rates, feeding into Workday.
Price Optimization Model
Maximizes margin by testing price elasticity with Bayesian models, connected to Magento or Shopify.
We build for every business type.
SaaS and Tech
Retail and Ecommerce
Manufacturing and Supply Chain
Financial Services
Healthcare and Pharma
Why businesses switch to AI forecasting
Manual Excel models fail when data grows past 10,000 rows.
Spreadsheets can't capture nonlinear patterns in sales cycles or seasonality. IRPR replaces your static sheets with a model that retrains weekly on fresh data, catching shifts before they hit your P&L.
A single Python script can process 5 years of transaction data in minutes, not hours. We've seen CFOs cut forecasting time from 3 days to 20 minutes after switching to our automated pipelines.
Custom AI vs. off-the-shelf forecasting tools
Generic tools like Tableau can't model your unique business logic.
Off-the-shelf forecasting software forces your data into pre-built templates. If your sales cycles depend on trade show calendars or regional promotions, those patterns get ignored.
IRPR builds a model that learns your specific lead-to-close timelines, seasonal quirks, and even competitor pricing effects. The result is a forecast that actually matches your board deck.
- Rigid templates that ignore your data structure
- No custom feature engineering
- Black-box models you can't audit
- Vendor lock-in with monthly fees
- Limited to pre-built integrations
- No dedicated support for model drift
- Custom model built on your historical data
- Feature engineering tailored to your KPIs
- Full transparency: you own the model and code
- Fixed price, no recurring license fees
- API connects to any internal system
- Ongoing retraining and monitoring included for 6 months
How we build your forecasting model
Every project follows a 4-phase process from data to dashboard.
Phase 1 starts with a data audit where we ingest your CSV, SQL, or API data and clean outliers. The audit report lists 20+ data quality checks.
By Phase 4, your team gets a production dashboard and 4 live training sessions. We deploy on your AWS or our SOC 2 cloud with a full runbook.
What ships with your forecasting project
You receive more than just a model. Every project includes:
All IRPR forecasting engagements come with full source code, documentation, and 6 months of support. You get everything needed to run and audit the system independently.
- Trained model in .pkl or .h5 format
- REST API with Swagger docs
- React dashboard source code
- CI/CD pipeline on GitHub Actions
- AWS CloudFormation deployment scripts
- Data preprocessing notebooks
- Model performance report (MAE, RMSE)
- 6 months of model retraining
- Integration with your data warehouse (Snowflake, BigQuery)
- User acceptance testing (UAT) environment
What we ship in this practice.
Revenue Forecasting for a SaaS Company
A CFO reduced quarterly close time from 5 days to 2 hours by automating MRR projections. Tech: Python, Prophet, React, Stripe API.
Demand Forecasting for a Retail Chain
A 200-store retailer cut stockouts by 35% using SKU-level demand predictions. Tech: TensorFlow, BigQuery, Tableau.
Cash Flow Prediction for a Fintech Startup
A fintech CEO avoided 3 cash crunches by forecasting 90-day runway with 95% accuracy. Tech: XGBoost, Plaid, QuickBooks API.
Inventory Optimization for a Manufacturer
A factory reduced holding costs by $120K/year by predicting raw material needs. Tech: PyTorch, SAP ERP, Power BI.
Patient Volume Forecasting for a Hospital Network
A 3-hospital system staffed 20% more nurses during flu season using ER visit predictions. Tech: Prophet, Cerner EHR, Tableau.
Churn Prediction for a Media Streaming Service
A streaming platform reduced cancellations by 18% by identifying at-risk subscribers early. Tech: XGBoost, Snowflake, Braze.
Why teams hire us.
Fixed price, not hourly
Every AI forecasting project gets a fixed quote after the data audit (week 2). No open-ended billing, no surprise invoices.
You own the model and code
All IP transfers to you at launch. No vendor lock-in, no proprietary black boxes.
Senior data scientists only
Your project is built by PhD-level ML engineers with 8+ years of experience. No junior devs learning on your dime.
6 months of free retraining
Models drift. We retrain yours monthly for 6 months post-launch at no extra cost.
SOC 2 compliant infrastructure
Your data stays on encrypted AWS instances with audit logging. We sign BAAs for healthcare clients.
10-week deployment
From signed contract to production dashboard in 10 weeks. We parallelize data engineering and frontend builds.
Idea → Roadmap → Product → Release.
Every engagement runs through the same four-stage pipeline. Predictable by design.
Questions clients ask first.
Related services and industries.
Ready to build? Let's talk.
30-minute discovery call. No deck. We'll tell you honestly what it takes, how long, and how much.