Get Started with Cleo
Welcome to the Cleo ecosystem developed by Inserloft.
Cleo is focused on:
- Programming
- Edge AI
- Mobile inference
- Efficient deployment
- Modern AI systems
The ecosystem is designed around specialized AI models optimized for different real-world environments and workloads.
What is Cleo?
Cleo is the AI ecosystem created by Inserloft.
Rather than building a single universal model for every possible task, Cleo is designed as a family of specialized AI systems optimized for:
- efficiency,
- reasoning,
- deployment,
- and scalability.
Our goal is to create AI systems that are practical, deployable, and accessible across modern hardware environments.
The Cleo Model Family
Cleo NaNo
Cleo NaNo is a lightweight AI model focused on:
- programming,
- edge AI,
- mobile inference,
- and efficient local deployment.
Features
- Lightweight architecture
- Optimized inference
- Programming-oriented reasoning
- Fast deployment
- Efficient local execution
Latest Improvements
- 22M → 52M parameters
- Better code understanding
- Improved context retention
- Conversational stability
- Faster inference optimization
Model Page
https://huggingface.co/Inserloft/NaNo
Cleo Kyro
Cleo Kyro is an advanced reasoning model designed for:
- broader intelligence,
- deeper context understanding,
- and stronger conversational reasoning.
Capabilities
- Advanced reasoning
- Conversational intelligence
- Context understanding
- Scalable architecture
- Modern optimization
Model Page
https://huggingface.co/Inserloft/Kyro
Real-World Deployment
The Cleo ecosystem is designed for modern AI deployment across multiple environments.
Programming
AI systems optimized for technical workflows and software development.
Edge AI
Lightweight deployment for local and edge environments.
Mobile Inference
Optimized models designed for modern mobile hardware and applications.
Open Ecosystem
Developer-focused experimentation and open-source releases.
Open Source
Inserloft currently supports open-source releases for:
- experimentation,
- local inference,
- deployment workflows,
- and developer tooling.
Available formats may include:
- GGUF
- safetensors
- PyTorch checkpoints
Our goal is to help developers:
- build,
- experiment,
- deploy,
- and integrate AI systems more efficiently.
Ecosystem Overview
This approach allows Inserloft to optimize AI systems for different workloads instead of relying on a single oversized model.
What’s Next
Development of the Cleo ecosystem is ongoing.
Future updates will continue improving:
- reasoning capabilities,
- context handling,
- inference speed,
- deployment tooling,
- mobile optimization,
- and programming intelligence.
Additional documentation, APIs, and developer tools will continue expanding over time.
Useful Links
Hugging Face
https://huggingface.co/Inserloft
