Brought to you by AdoptAI: Bridging the gap between cutting-edge AI research and real-world deployment.

The AI Container Store helps organizations become AI-first with a structured on-ramp for adopting, refining, and deploying AI solutions. Our modular approach combines containerized algorithms, education, and expert guidance to accelerate practical and impactful AI adoption.

Repository	Description	Status
[AdoptAI-Demo-ImageClassification]	An end-to-end CNN built from scratch for image classification
[AdoptAI-Demo-NLP]	Fine-tuned LLM for summarization & Q&A
[AdoptAI-Demo-TimeSeries]	Time-series forecasting for demand & resource planning
[AdoptAI-Demo-ObjectDetection]	Pretrained object detection model (YOLOv5) with real-time inference
[AdoptAI-Demo-LiquidNets]	Experimental continuous-time neural networks for advanced temporal tasks
[AdoptAI-Demo-Recommender]	Personalized recommendation engine using collaborative filtering

Each demo project illustrates a different facet of AI adoption—whether training from scratch, fine-tuning, or off-the-shelf inference. Explore them to learn best practices and accelerate your AI journey.

1. Containerized AI Modules: Quick deployment of various models—vision, NLP, time-series, generative AI—via Docker or Kubernetes.
2. AI Education and Seminars: Workshops, hackathons, and tailored training sessions to empower teams with modern AI know-how.
3. Expert Guidance: Leverage the collective experience of AdoptAI specialists who bring extensive domain knowledge in MLOps, model lifecycle, and enterprise integration.
4. Agentic Investor Vision: Special support for VC firms seeking an edge in sourcing AI-first startups and guiding their portfolio companies.

This .github repository hosts community health files, issue templates, and organization-wide configurations:

• README.md: You’re reading it now! The central introduction to AdoptAI.
• CONTRIBUTING.md: Guidelines for contributing to our projects.
• CODE_OF_CONDUCT.md: Our commitment to an inclusive, welcoming environment.
• ISSUE_TEMPLATE/: Templates to standardize bug reports, feature requests, etc.

Note: Each demo repository has its own dedicated docs and code structure. See the individual README files for details on usage, setup, and model architecture.

1. Clone & Explore: Pick a demo project and test it locally to understand how we build and deploy AI solutions.
2. Open Issues or PRs: Spot a bug or have a brilliant idea? Contribute your improvements!
3. Join Discussions: We welcome questions, suggestions, and brainstorming in the Discussions tab.
4. Spread the Word: If you find our resources valuable, star the repos and share them with your network.

• Expand AI Demo Catalog: Add more advanced use cases (reinforcement learning, advanced generative modeling, etc.).
• MLOps Integration: Offer templates for CI/CD pipelines, model monitoring, and automated testing.
• Enterprise Blueprint: Develop a reference architecture for large-scale deployments, focusing on security and compliance.

Join our Slack Channel (placeholder link) to stay updated on events, meet fellow AI enthusiasts, and get expert tips. If you need enterprise support or custom integrations, check out our AdoptAI website (placeholder link) or reach out via email.

Unless otherwise stated, all code within the The AI Container Store GitHub organization is released under the MIT License. You’re free to fork, modify, and build upon our work for both commercial and non-commercial use—just please give us credit!

Thank You for Visiting The AI Container Store
We’re on a mission to demystify AI adoption and help organizations leverage the next wave of intelligent applications. We can’t wait to see what you’ll build with us!