Introduction

Timefold Platform is a managed service for running Timefold optimization models through a REST API. It removes the need to manage infrastructure yourself, and gives problem owners the right tools and insights to integrate, validate, and continuously improve their planning solutions.

The Timefold team has built enterprise-ready models that include extensive input validation, visualization tools, integrations such as maps services, that are ready to scale. Available models include Field Service Routing, Employee Shift Scheduling, and Pick-up and Delivery Routing. See Model catalog and documentation for the full list, including trial access.

The platform is organized in four layers, each building on the one beneath it. Starting from the infrastructure that runs the solver, up to the intelligence that turns every plan into business evidence.

Hosting and orchestration

Building a production-ready optimization model is more than embedding a solver library. You also need to host it, scale it, queue requests, deliver results reliably, manage credentials, and keep data secure per tenant. Timefold Platform handles all of that and exposes models as a managed REST API, so your team ships integrations, not infrastructure.

The Hosting and orchestration layer runs the solver APIs in the cloud, auto-scales to your request volume, prioritizes and queues requests, and delivers results via webhooks, server-sent events, or polling. Your data stays encrypted and isolated per tenant, with 24/7 monitoring and automatic backups.

Integrations

Timefold exposes clean REST endpoints that plug into your existing enterprise systems, including ERPs, HRIS, CRMs, and field-service tools, without replacing them. Problems are submitted as JSON in domain-specific shapes with clear validation and error handling.

Real-time replanning handles operational changes (sick calls, urgent jobs, traffic) the moment they happen, with incremental updates instead of full resubmissions and freeze options to protect in-progress work, minimizing disruption to ongoing operations. Geospatial services provide pre-calculated distance and travel matrices supporting multiple vehicle profiles.

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Explainability and trust

Optimization projects fail not because of mathematical shortcomings, but because people won’t trust the result.

Timefold’s Explainability and trust layer bridges the gap between "I don’t know what this is" and "I see why." Every assignment, tradeoff, and exception has documented reasoning. When no feasible solution exists, the system identifies exactly which constraint, resource, or input caused the problem. Planners can pin assignments, override decisions, and immediately see how the plan responds.

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Intelligence

Most schedulers hand you a plan and stop there. Intelligence picks up where they stop, turning every plan into evidence about what’s working, what’s hiding, and what would change if you reshaped the operation.

Scheduling becomes evidence-based rather than intuition-driven. Planners design instead of constantly revising. Operations teams make data-driven decisions instead of anecdotal ones.

  • Dataset comparison to evaluate and benchmark results across different datasets and configurations

  • Configuration profiles to reweight optimization priorities (cost, fairness, service quality, environmental impact) without code changes

  • Insights tracks KPI trends across datasets over time, so you can spot whether key metrics are improving or degrading and whether a model update has affected solution quality

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