EvenFlow AI provides a cloud‑based scheduling platform that uses AI and operations‑research algorithms to allocate service appointments based on technician capacity, bay availability, and skill sets. The system continuously re‑optimizes for walk‑ins, cancellations and emergencies, and offers a dashboard with utilization, revenue and wait‑time analytics to help service managers maximize throughput.
Funding
$1.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Automotive dealerships often schedule service appointments manually, resulting in uneven technician workloads—peak periods cause overrun and long customer wait times, while off‑peak periods leave technicians idle. This imbalance prevents many shops from capturing their full service revenue potential, typically realizing only about 70% of what could be earned.
Solution
EvenFlow AI offers a cloud‑based scheduling platform that applies AI and operations‑research algorithms to balance service lane load against each technician’s capacity. By analyzing historical demand, service bay constraints, and technician skill sets, the system generates appointment slots that keep the shop evenly paced throughout the day. Real‑time adjustments accommodate last‑minute changes, ensuring optimal utilization without overburdening staff. Managers receive a dashboard that visualizes projected revenue, technician productivity, and customer wait times, enabling data‑driven decisions to boost service gross and satisfaction.
Target Audience
The primary customers are service managers and operations leaders at franchised automotive dealerships seeking to improve technician productivity and capture additional service revenue.
Features
- AI‑driven scheduling engine that optimizes appointment placement based on fixed technician capacity and service bay availability
- Capacity‑based load balancing using proven techniques from airline revenue management to maximize throughput
- Real‑time re‑optimization for walk‑ins, cancellations, and emergency repairs
- Predictive demand forecasting that incorporates historical service patterns and seasonal trends
- Configurable business rules (e.g., service type priorities, technician skill matching, buffer times)
- Integration APIs for major dealer management systems (CDK, Reynolds & Reynolds, Tekion, etc.)
- Interactive analytics dashboard showing projected revenue uplift, technician utilization, and average customer wait time
- Cloud‑hosted SaaS architecture with role‑based access control and encrypted data storage