Agenia Pro is an innovative platform for technical teams and data researchers, offering: 1.: Automates tasks and manages scripts securely. 2. : Safe testing and development. 3. **Advanced Security**: Data confidentiality. 4. **Language Models**: Real-time analysis and automation. 5. **Document and Image Analysis**: Comprehensive insights. 6. **Voice and Microphone**: Seamless conversational interaction. Ideal for technical teams, data researchers, and users needing a conversational assistant.
Hello everyone! I know you're always looking for solutions to improve your workflow and tackle complex project challenges. I'm excited to introduce AgenIA PRO, a platform that will revolutionize the way we interact with AI in our projects. With this web app from DataCorners.com, you can use a multi-provider AI agent that seamlessly integrates with popular services like OpenAI, Qwen, DeekSeek, OpenRouter, Anthropic, Cohere, AI21 Labs, and Google AI. Our platform gives you full control over your interactions with AI, simplifying the setup of your dashboards and data pipelines. Whether you're an experienced developer or just starting out, DataCorners makes it easy to install and manage Git modules and projects for optimal auditability. Our multi-provider AI agent offers a smooth experience, allowing you to leverage the best features of multiple AI services in a user-friendly interface. Additionally, DataCorners provides voice and video functionalities, offering a natural and intuitive user experience. Join our community now and be among the first to explore the infinite possibilities offered by DataCorners at launch! [Join our community now →](https://datacorners-local.com)
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How does it actually handle the local vs cloud switching — is that automatic based on task complexity or do I have to manually configure which models run where?
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Maker
@eymengur6 It could be à new feature so, the switching between local and cloud is not automatic. We maintain control over the agent, and the switching happens only upon the user's request. This ensures that you have full control over where and when the models run. regards :).
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How does the local version handle model updates when new language models drop, and is there any catch to running the cloud tier alongside it without duplicating data?
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Maker
@melahatemicyh7 Data is not duplicated when switching from local to cloud. The locally hosted model at the end client's site is by definition integrated by us but managed by the client if they wish, thus benefiting from 100% controlled privacy. For cloud updates, our partners will be able to update their models, allowing them to remain competitive as well. I would like to highlight that our next local model is currently in research and development, it will benefit from efficiency in both consumption and reflection, giving us a considerable lead over our competitors. Our micro AI is capable of playing a game of poker that lasts between 40 minutes and 1 hour! but that is another topic. Best regards.
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Curious how the local version actually handles the heavier model loads, like does it run smoothly without a beefy GPU or will it choke on anything beyond basic tasks?
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How does it actually handle the local vs cloud switching — is that automatic based on task complexity or do I have to manually configure which models run where?
@eymengur6 It could be à new feature so, the switching between local and cloud is not automatic. We maintain control over the agent, and the switching happens only upon the user's request. This ensures that you have full control over where and when the models run. regards :).
How does the local version handle model updates when new language models drop, and is there any catch to running the cloud tier alongside it without duplicating data?
@melahatemicyh7 Data is not duplicated when switching from local to cloud. The locally hosted model at the end client's site is by definition integrated by us but managed by the client if they wish, thus benefiting from 100% controlled privacy. For cloud updates, our partners will be able to update their models, allowing them to remain competitive as well. I would like to highlight that our next local model is currently in research and development, it will benefit from efficiency in both consumption and reflection, giving us a considerable lead over our competitors. Our micro AI is capable of playing a game of poker that lasts between 40 minutes and 1 hour! but that is another topic. Best regards.
Curious how the local version actually handles the heavier model loads, like does it run smoothly without a beefy GPU or will it choke on anything beyond basic tasks?