Define the workload
Describe your model, workload, performance targets, and deployment requirements.
From experiment
to production. Connected.
Manage experiments, model artifacts, evaluations, and deployment in one workflow. Track each release from its training configuration to its production behavior.
01
Version the workflow.
Define model objectives, evaluation criteria, and performance targets in configuration you can inspect, review, and version.
02
Trace every release.
Keep checkpoints, benchmarks, and validation results with the model. Compare releases and trace each change back to its experiment.
03
Learn from production.
Feed observed quality, latency, and resource use back into evaluation. Use real workload behavior to prioritize the next optimization.
THE DEVELOPER WORKFLOWEvery stage.
Every stage.
One configuration.
Set the objective, define evaluations, choose optimization targets, and specify deployment. Select a stage to explore the configuration preview.
PROFILE THE WORKLOAD
Explore the optimization pipelineBenchmark your workload.
Measure quality, latency, throughput, and resource use against representative inputs. Set a reproducible baseline for every optimization that follows.
1# URPX model pipeline
2# Illustrative configuration
3
4project: intelligent-product
5model: ./models/checkpoint
6
7pipeline:
8 focus: measure
9 build:
10 objective: fine-tune
11 evaluate:
12 dataset: ./evals/workload
13 optimize:
14 priorities: [latency, throughput]
15 preserve: quality
16 deploy:
17 artifact: validated-model
18 target: selected-environment
19
20feedback:
21 source: production-observations
CONFIGURATION PREVIEW · NOT A PUBLISHED API
DEVELOPER EARLY ACCESSBring your workload.
Bring your workload.
Build with us.
Validate the pipeline
Benchmark the workload, evaluate optimization candidates, and confirm the deployment path.
Integrate the platform
Access developer tools, versioned interfaces, and integration guidance as they become available during early access.