Open-source infrastructure.

Tandemn Enterprise is our paid offering for operating fleet-wide planning in production. It combines direct engineering support, advanced observability, governance and security capabilities, and performance learning across deployments. These capabilities give infrastructure teams a supported path from integration to ongoing operation, with the visibility to measure recovered capacity, maintain serving targets, and manage GPU spend as demand grows.

Tandemn’s research and systems engineers lead integration of the planner and execution engine with your existing inference stack. We replay workload traces, validate configurations and placements in a sandbox, and compare capacity, latency, throughput, and cost against your baseline before fleet-wide deployment. The engagement establishes the infrastructure interfaces, serving targets, and operational constraints needed to run planning within your environment.

Enterprise customers work directly with the engineers responsible for Tandemn’s planning algorithm and execution system. We diagnose serving behavior, investigate prediction errors, and tune planning as your models, demand, and hardware change. This ongoing technical partnership gives your infrastructure team the expertise to resolve fleet-specific issues and sustain capacity gains while managing the performance and cost of production inference.

Extended telemetry connects each plan’s configurations, allocations, and placements to observed latency, throughput, and cost. Your team inspects predicted versus actual performance, serving risk, and model uncertainty to understand how decisions affect individual workloads and the fleet. This evidence supports systematic diagnosis and tuning, with a measurable basis for evaluating recovered capacity, serving target attainment, and the economics of your inference infrastructure.

Enterprise governance and security capabilities bring your organization’s operational requirements into fleet-wide planning and execution. We align the integration with your infrastructure policies, deployment practices, and constraints governing shared resources. Your team retains control over the environment while working with Tandemn to define how optimization operates within it, establishing a consistent operational framework for introducing planning across business-critical inference workloads.

Enterprise planning draws on anonymized performance observations across Tandemn deployments, extending its evidence beyond a single fleet. Relationships between model characteristics, GPU hardware, serving configurations, and observed outcomes inform performance predictions and future planning decisions. This broader evidence base supports configuration and placement decisions when your team introduces new models or resources, building on experience accumulated across a wider range of inference environments.