⭐ Trusted by over 150,000 ML practitioners

The Fastest Path to Models That Ship

GradientPond connects experiment tracking to deployment, automatically turning training insights into production-ready models.

Try GradientPond Free View Docs →

Trusted by over 150,000 developers and thousands of companies

GradientPond — Experiment Dashboard

94.2%

Best Acc

0.031

Loss

847

Epochs

2h14m

Time

Log & organize every experiment automatically

Add two lines of code and GradientPond captures metrics, hyperparameters, code state, and artifacts for every training run.

Try GradientPond free →

Run #847 — resnet50-v3

lr: 0.001

batch: 64

opt: AdamW

epochs: 100

✓ Metrics · ✓ Git a3f2c1d · ✓ Env captured

Run	Acc	Loss	LR
run-3 ★	94.2%	0.031	0.001
run-2	92.8%	0.045	0.003
run-1	89.1%	0.082	0.01

Easy Integration

Two lines of code. Full observability.

Works with every major ML framework. No config files, no complex setup.

LLM Evaluation

Any LLM LlamaIndex LangChain OpenAI

ML Frameworks

PyTorch TensorFlow Hugging Face

 import gradientpond as gp
2
 @gp.track
 def train_model(config):
   model = build_model(config)
   for epoch in range(config.epochs):
     loss = train_epoch(model)
     gp.log_metric("loss", loss)
   return model

Try GradientPond Free View on GitHub →

An End-to-End ML Evaluation Platform

GradientPond's platform for ML teams focuses on shipping models faster, including experiment tracking, evaluations, model registry, and production monitoring.

Compare (2)

Track & Compare Training Runs

Log metrics, hyperparameters, and artifacts. Compare unlimited runs with interactive visualizations and parallel coordinates.

correctness 0.95 score 0.88 hallucination 0.12

Evaluate & Score Model Outputs

Built-in eval metrics, LLM-as-a-judge scoring, and custom evaluation rubrics. Catch regressions before they reach production.

Model Registry & Versioning

Version models with full lineage. Stage gates from development to production with approval workflows and CI/CD integration.

99.9%

4.1s

$0.23

uptime

latency

cost/req

Production Monitoring

Real-time monitoring for data drift, model degradation, and cost tracking. Automated alerts when metrics breach thresholds.

Built for Enterprise, Driven by Community

GradientPond's platform is trusted by innovative ML teams in the most demanding environments.

Autonomous Systems

"GradientPond has aided our success with ML and serves to further model development across our entire autonomous driving division."

Kyle AndersonDirector of ML Engineering

FinTech Corp

"GradientPond offers the most complete experiment tracking solution on the market. It's brought significant value to our fraud detection models."

Olcay CiritStaff Research & Tech Lead

HealthAI

"GradientPond enables us to speed up research cycles and reliably reproduce and collaborate on our modeling projects. Indispensable."

Victor SanhMachine Learning Scientist

The Fastest Path to Models That Ship

Log & organize every experiment automatically

Compare runs side-by-side with rich visualizations

Evaluate models with automated test suites

Deploy models through staging gates

Monitor model performance in production