Meta has made it official: With the release of the open-source model Llama 4 Scout, a new era begins for companies that process sensitive data while wanting to benefit from powerful AI. The model offers a 10-million-token context window and runs on just a single GPU. This means:
Enterprise AI without cloud, without data risk, without quality loss.
Llama 4 Scout: Technological Milestone for Industry
The new Llama 4 portfolio includes three models:
- Scout (17B parameters): Optimized for deep document analysis with massive context.
- Maverick (400B parameters): Outperforms GPT-4o and Gemini 2.0 in many areas.
- Behemoth (2 trillion parameters, still in training): Focus on math & STEM.
What makes it special: Even the Scout model is multimodal, understanding both text and image, and can be run locally on just a single GPU. This makes it ideal for deployment directly on company premises.
Finally: Your Own Enterprise AI -- GDPR-Compliant and Efficient
Many companies shy away from AI integration because cloud solutions come with data privacy risks. With Llama 4 Scout, that is history:
Companies can now operate their own Large Language Model directly on-premise -- fully under their own control.
And this has enormous advantages:
- No sensitive data leaves the company
- Full control over training, access rights, and output
- No dependency on third-party providers or black-box systems
AI Deployment Where It Really Counts!
Industrial companies in particular suffer from the skilled labor shortage. Engineers today spend far too much time on repetitive tasks such as:
- Writing protocols
- Creating quotation comparisons
- Searching through technical reports
- Preparing documents for audits
This blocks valuable capacity for research, development, and innovation.
Agentic Workflows + On-Premise LLMs = Productivity Boost
This is exactly where Ziya steps in: With Agentic Workflows and individually trained LLMs installed directly in the company, we free specialists from repetitive documentation work.
The model draws on:
- Historical project data
- Current standards & regulations
- Domain-specific expertise
to automatically create inspection reports, protocols, quotations, or summaries -- precisely, scalably, and in full data privacy compliance.
Every Company Becomes an AI Company
Many companies already have massive amounts of data. But instead of viewing this as a digitalization burden, AI can finally make it productive.
With the right setup, this evolves into a genuine AI culture. The focus is not on individual use cases, but on a long-term transformation into an AI company:
- Lower costs, higher efficiency
- Less manual work, more focus on innovation
- Competitiveness for decades to come
Conclusion: Those Who Don't Act Now Will Be Left Behind
The technological leap that Llama 4 Scout enables is massive. What once required million-dollar budgets is now accessible to SMEs and hidden champions.
The time is ripe to start your own AI initiatives and relieve specialists where AI has its greatest leverage: in the repetitive daily routine.
Now is the moment to establish your own AI in the company. Ziya shows you how.