- AI Developers: Building and deploying AI applications.
- MLOps Engineers: Managing the lifecycle of machine learning models.
- Data Scientists: Working with LLMs, vector databases, and Jupyter notebooks.
- Businesses & Enterprises: Seeking to deploy AI solutions in a self-hosted, secure, and scalable manner.
- Organizations: Aiming to avoid vendor lock-in for their AI infrastructure.
- DevOps Teams: Responsible for setting up and maintaining AI deployment environments.
How to Use Batteries Included?
- Sign Up: Begin with seamless onboarding to quickly set up your environment.
- One-Click Deployments: Utilize one-click deployments to instantly launch production-ready LLMs (like Ollama, OpenWebUI) and vector databases (like PGVector).
- Local Setup (Optional): For local deployments, execute a provided script (e.g., `/bin/bash -c "$(curl -fsSL https://home.batteriesincl.com/api/v1/scripts/start_local)"`).
- Integrate: Integrate with your existing tech stack without the need for extensive YAML configuration.
- Develop & Monitor: Use the complete MLOps and AI development stack (including MLflow) and leverage advanced monitoring and self-healing systems.
- Self-Hosted Infrastructure: Provides a complete AI infrastructure that users can self-host, offering greater control and data privacy while eliminating vendor lock-in.
- Hyperscaler Tools for Self-Hosting: Offers the same high-end tools used by hyperscale cloud providers (like LLMs, vector databases, MLOps stack) but optimized for self-hosted environments.
- One-Click Deployments: Simplifies complex deployments of production-ready LLMs and vector databases with just a single click.
- Seamless Integration: Designed to integrate easily with existing tech stacks without requiring complex YAML configurations.
- Comprehensive MLOps & AI Dev Stack: Includes essential tools like MLflow and model registries for a complete development and operational workflow.
- Enterprise-Grade Security & Scalability: Features industry-leading security (SSO, automated SSL), dynamic autoscaling for serverless apps, and cost-effective blue/green canary deployments.
- Offers full control and avoids vendor lock-in through self-hosting capabilities.
- Simplifies the deployment of complex AI components like LLMs and vector databases with one-click solutions.
- Integrates seamlessly with existing technology stacks without demanding extensive configuration.
- Provides a comprehensive MLOps and AI development stack, including MLflow.
- Ensures high security with features like SSO and automated SSL.
- Features dynamic autoscaling and cost-effective blue/green deployments for efficient scaling.
- Includes advanced monitoring and self-healing systems for reliable operations.
- Requires self-hosting, which implies users need technical expertise to manage their own infrastructure.
- Specific pricing details or subscription tiers are not explicitly provided on the browsed page.
- While "seamless onboarding" is mentioned, the underlying complexity of self-hosting an AI platform might still be challenging for less technical users.
- The benefits of "cost-effective scaling" are stated, but without comparative data or case studies.
Free Plan
$ 0.00
Small cluster deployment (up to 3 nodes)
Single-node Docker development environment
Full platform capabilities
Powerful and intuitive user interface
Built on enterprise-grade open source technologies
Premium Plan
$ 30.00
Scale beyond 3 nodes for production workloads
Simple usage-based pricing for production environments
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TextCortex
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Editorial Note
This page was researched and written by the ATB Editorial Team. Our team researches each AI tool by reviewing its official website, testing features, exploring real use cases, and considering user feedback. Every page is fact-checked and regularly updated to ensure the information stays accurate, neutral, and useful for our readers.
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