Frequently Asked Questions

Getting started is easy! Sign up for an account and upload your historical call data. Standard tier and above include self-service onboarding with documentation and email support. Professional and Enterprise tiers can add white-glove setup for personalized assistance.
To generate accurate predictions, we need historical call/incident data including timestamps, call types, and durations. The more historical data you provide (ideally 2+ years), the more accurate our predictions will be. We also incorporate weather data and local event information automatically.
Sign up in 90 seconds and get your first predictions in under an hour. Upload your historical data, configure your shift schedules, and you're ready to go.
Yes! We offer a free trial period where you can upload sample data and see how our predictions work for your agency. Contact our sales team to set up a personalized demo and trial.

Our predictions typically achieve 85-95% accuracy depending on the agency and data quality. Accuracy improves over time as the model learns from your specific patterns. We continuously validate predictions against actual outcomes and refine the models.
Our AI models analyze historical call patterns, time of day, day of week, seasonal trends, weather conditions, local events, holidays, and other relevant factors. The model learns the unique patterns of your specific jurisdiction.
Our short-term model provides predictions for the next 15 days, updated daily for maximum accuracy. Long-term forecasts extend over a year depending on your service tier—see our Pricing page for tier-specific prediction horizons.
First, validate that your imported data was parsed correctly. If issues continue, contact support and we'll investigate. We retain multiple prediction versions as our models improve, allowing you to track accuracy over time.
Yes! Our feedback system allows you to flag predictions that don't match reality. This feedback helps improve model accuracy over time. You can also add notes about special circumstances that affected call volumes.