# Timefold

Timefold is an AI-powered planning and optimization platform that helps organizations solve complex scheduling, routing and resource planning problems. Its production-ready APIs and optimization models turn operational data, business rules and constraints into optimized plans for field service routing, employee shift scheduling, pickup and delivery routing, task scheduling and other planning use cases.

## Core APIs

- [Field Service Routing API](https://timefold.ai/products/field-service-routing): Assign visits to qualified field workers and optimize schedules and routes around travel, time windows, skills, and operational constraints.
- [Employee Shift Scheduling API](https://timefold.ai/products/employee-shift-scheduling): Assign employees to shifts while balancing coverage, availability, fairness, cost, and workforce rules.
- [Pickup & Delivery Routing API](https://timefold.ai/products/pickup-and-delivery-routing): Assign pickup and delivery jobs to drivers and vehicles while considering capacity, time windows, and travel.
- [Task Scheduling API](https://timefold.ai/products/task-scheduling): Sequence jobs and assign resources around dependencies, priorities, and availability.

## Technical documentation

- [Documentation home](https://docs.timefold.ai/): Start here for current platform, model, and solver documentation.
- [Timefold Platform](https://docs.timefold.ai/timefold-platform/latest/introduction): Managed models, REST API integration, and platform capabilities.
- [Field Service Routing documentation](https://docs.timefold.ai/field-service-routing/latest/introduction): Routing model and integration guidance.
- [Employee Shift Scheduling documentation](https://docs.timefold.ai/employee-shift-scheduling/latest/introduction): Workforce scheduling model and integration guidance.
- [Pickup & Delivery Routing documentation](https://docs.timefold.ai/pickup-delivery-routing/latest/introduction): Pickup and delivery model and integration guidance.
- [Task Scheduling documentation](https://docs.timefold.ai/job-scheduling/latest/introduction): Task scheduling model and integration guidance.

## Evaluation and next steps

- [Pricing](https://timefold.ai/pricing): Commercial options and evaluation path.
- [Customer stories](https://timefold.ai/customer-stories): Examples of customer implementations and results.
- [Timefold Solver](https://timefold.ai/solver): Open-source solver for teams building custom optimization models.
- [Solver documentation](https://docs.timefold.ai/timefold-solver/latest/introduction): Technical guide to the open-source solver.

## Vehicle routing problem

- [Vehicle Routing Problem (VRP) guide](https://timefold.ai/vehicle-routing-problem): Explains the vehicle routing problem, common variants and constraints, approaches to solving it, and how Timefold's routing APIs apply to real operations.

## Additional resources

- [Blog](https://timefold.ai/blog/): Explanations, product updates, and practical routing and scheduling guidance.