Plans & Pricing
Your Tools, Your Terms
Get your models into production with no wasted spend or unnecessary complexity. With flexible support and modular add-ons, you can scale confidently when your needs evolve.
Open Source tool for DevOps and ML Engineers to deploy ML models in simple environments. MLServer is a lightweight inference server for your machine learning models.
Features
- API Access
- Lightweight Inference Serving
- Pre-packaged Runtimes
- BYO Custom Runtimes
- Model Serving
Support
Accelerator programs including hands-on support plus the option to add modules, to ensure your machine learning projects are set up and maintained efficiently.
Features
- MLServer
- API Access
- Lightweight Inference Serving
- Pre-packaged Runtimes
- BYO Custom Runtimes
- Model Serving
- Experimentation
- CLI Access
- Production Model Serving
Support
- Customer Success Manager
- Response Time SLA
- 9-5 GMT or ET Support
- Support Portal
- Annual Health Check
- Warranted Binaries
- IQ Sessions
- Slack Community
- Documentation
Module Add On
- LLM Module
- MPM Module (Early Access)
- Alibi Detect
- Alibi Explain
Modular framework with a data-centric approach, designed to harness the growing complexities of real-time deployment and monitoring.
Features
- MLServer
- API Access
- Lightweight Inference Serving
- Pre-packaged Runtimes
- BYO Custom Runtimes
- Model Serving
- Experimentation
- CLI Access
- Production Model Serving
Support
Licensing
Modular Add‑Ons for Maximum Flexibility
Add-On
Add powerful explainability tools to your production ML pipelines, including a wide range of algorithms to understand model predictions for tables, images, and text covering both classification and regression.
Includes
- Comprehensive Explainability Coverage
- Storage and Portability
- Benefit from Seldon’s Ecosystem
Add-On
Add real-time and batch monitoring to your ML pipelines, spotting drift, outliers, and adversarial inputs across all data types. It helps teams boost model quality, build trust, and meet global AI regulations.
Includes
- Comprehensive Detection Coverage
- Pretrained Models and Supported Datasets
- Model- and Context-Aware Detection
- Benefit from Seldon’s Ecosystem
Add-On
Core+ Customers
Simplify the deployment, support for common design patterns (RAG, prompting, and memory) and lifecycle management of Generative AI (GenAI) applications and LLMs.
Includes
- Deployment with Standardized Prompting
- Agents and Function Calling
- Embeddings and Retrieval
- Memory and State Management
- Operational and Data Science Monitoring
- Benefit from Seldon's Ecosystem
Add-On
Early Access for Core+ Customers
Model Performance Metrics (MPM) Module enables data scientists and ML practitioners to optimize production classification & regression models with model quality insights.
Includes
- Comprehensive Metric Coverage
- Feedback Storage and Linking
- Time-Based Trend Analysis
- Model Quality Dashboards
- Benefit from Seldon’s Ecosystem
From Dreamto Deployed
Seldon’s LLM Module on top of Core+ is the next step in your AI evolution through effortless deployment and scalable innovation.
Take Control of Real-Time Machine Complexity
Deploy Anywhere, Innovate Freely
Freedom to build and deploy ML your way, whether on-prem, in the cloud, or across hybrid stacks.
With support for traditional models, custom runtimes, and GenAI frameworks, Seldon fits your tech, your workflows, and your pace without vendor lock-in.
Learn Once, Apply Everywhere
Scale confidently with a unified deployment process that works across all models, from traditional ML to LLMs.
Seldon eliminates redundant workflows and custom containers, enabling your teams to launch faster, reduce errors, and scale ML consistently.
Visibility with Zero Guesswork
Get real-time insights into every model, prediction, and data flow no matter how complex your ML architecture.
From centralized metric tracking to step-by-step prediction logs, Seldon empowers you to audit, debug, and optimize with complete transparency.
Maximize Impact, Minimize Waste
Our modular framework scales dynamically with your needs, no overprovisioning, no unused compute.
Features like Multi-Model Serving and Overcommit help you do more with less, cutting infrastructure costs while boosting throughput. Efficient by design, Seldon ensures your investments deliver oversized returns.
Core 2 Architecture
Seldon Core 2 leverages a microservices-based architecture with two layers:
Manage inference servers, model loading, versioning, pipeline configurations, running experiments, and operational state to ensure resilience against infrastructure changes
Handle real-time inference requests using REST and gRPC protocols with the Open Inference Protocol (OIP) and are powered by Envoy for intelligent routing
It also enables interoperability and integration with CI/CD and broader experimentation frameworks like MLflow by Databricks and Weights & Biases.
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