Neptune.ai
Neptune.ai
What is Neptune.ai?
Make every model decision searchable, comparable, and auditable
Key Capabilities
What makes Neptune.ai powerful
SDKs and callbacks
Add a few lines to send metrics params and artifacts from PyTorch Keras XGBoost or custom loops into a searchable store.
Runs at scale
Use tags filters and charts to find the best runs and understand tradeoffs across experiments.
Versioned models
Promote versions through stages with approvals so rollback and audits are straightforward.
Enterprise controls
Adopt SSO private deployments and role based access to meet security and compliance needs.
Professional Integration
These capabilities work together to provide a comprehensive AI solution that integrates seamlessly into professional workflows. Each feature is designed with enterprise-grade reliability and performance.
Key Features
What makes Neptune.ai stand out
- Flexible logging: Track metrics params artifacts and images from any framework using light SDKs and callbacks
- Search and compare: Slice runs by tags configs and scores to pick winners with evidence not memory
- Custom dashboards: Build live charts tables and tiles to monitor long trainings and share status
- Model registry: Store versions stages and approvals so releases are auditable and reversible
- Collaboration: Organize workspaces projects and roles so large teams stay coordinated
- Artifacts: Keep predictions checkpoints and plots alongside metrics for reproducibility
- SSO and privacy: Use enterprise auth and private deployments for regulated environments
- Integrations: Connect notebooks CI and orchestration tools for end to end workflows
Use Cases
How Neptune.ai can help you
- Track baselines and ablations to defend decisions in reviews
- Monitor long running experiments and intervene when metrics drift
- Promote models through staged approvals with clear lineage
- Share results with PMs and leads using links and dashboards
- Attach artifacts so future teams can reproduce findings quickly
- Automate comparisons in CI to block regressions before merge
- Centralize model metadata to satisfy audit requirements
- Create a living catalog of production models and research
Perfect For
ML engineers, researchers, data scientists, MLOps and platform teams who need reliable tracking and registries
Pricing
Start using Neptune.ai today
Starting price
Quick Information
Compare Neptune.ai with Alternatives
See how Neptune.ai stacks up against similar tools
Frequently Asked Questions
How does Neptune pricing start?
Does it work with my framework?
Is there a model registry included?
How does Neptune help with audits?
Can it run privately?
Similar Tools to Explore
Discover other AI tools that might meet your needs
Akkio
dataNo code AI analytics for agencies and businesses to clean data, build predictive models, analyze performance and automate reporting with team friendly pricing.
Algolia
dataHosted search and discovery with ultra fast indexing, typo tolerance, vector and keyword hybrid search, analytics and Rules for merchandising across web and apps.
Alteryx
dataAnalytics automation platform that blends and preps data, builds code free and code friendly workflows, and deploys predictive models with governed sharing at scale.
BentoML
codingOpen source toolkit and managed inference platform for packaging deploying and operating AI models and pipelines with clean Python APIs strong performance and clear operations.
FloydHub
specializedFloydHub was a managed training and deploying platform for deep learning experiments that simplified data mounting jobs metrics and collaboration but it permanently shut down in 2021.
Mystic.ai
codingMystic.ai is an AI model deployment platform offering serverless endpoints and a bring your own cloud option, with Python SDK oriented workflows, OAuth based cloud integration, and scaling controls like min and max replicas and scale to zero, aimed at production inference without a large MLOps team.