Unlike subscription-based AI tools, Llama gives organisations access to the underlying AI model itself, making it possible to run AI privately, customise it around internal workflows and build tailored AI solutions. Developed by Meta, Llama stands out for its flexible and customisable AI ecosystem, making it a strong option for businesses looking to build tailored AI tools while maintaining control over data, infrastructure, and workflows.
Llama helps organisations build AI solutions that fit their own systems, workflows, and operational requirements, making it ideal for enterprises looking for flexibility and customisation.
Create tailored AI assistants, internal copilots, and support tools trained around your workflows and knowledge.
Deploy AI within a private cloud, enterprise, or on premise environment for organisations that require more flexibility around data management, governance, and deployment environments.
Llama can be embedded into existing platforms, tools, and business processes to support customised automation at scale.
Llama provides developers with greater flexibility to fine-tune models, customise behaviour, and build AI-powered applications.
Unlike closed AI platforms, Llama allows organisations to build and customise AI within their own environments.
Flexible Deployment Options
Use Llama across cloud platforms, enterprise infrastructure, or private environments depending on organisational requirements.
Customisation & Fine-Tuning
Customise models based on company data, workflows, terminology, and operational needs to create tailored AI experiences.
Scalable AI Infrastructure
Scale AI across internal systems, company data, and enterprise environments while maintaining greater control over performance, infrastructure, and workflows.
APIs & Open Ecosystem
Use APIs, frameworks, and integrations to build custom AI applications, automation workflows, and enterprise solutions.
Llama 4 Scout – Lightweight & Scalable
Designed for efficient AI workloads, fast deployment, and large context processing across enterprise and developer environments.
Llama 4 Maverick – General Purpose AI
Meta’s enterprise model for content creation, reasoning, coding assistance, workflow automation, and conversational AI applications.
Llama 4 Behemoth – Advanced Reasoning & Complexity
Meta’s most advanced Llama model for complex tasks, deep reasoning, research, technical workflows, and enterprise-scale AI applications.
Code Llama – Coding & Developer Workflows
Built for software development, code generation, debugging, and technical problem solving across developer environments.
Multimodal Llama Models – Text, Image & AI Workflows
Supports multimodal AI workflows across text, images, and advanced AI applications through Meta’s broader AI ecosystem.
Meta Llama is widely used by organisations, developers, and AI teams looking to build customised AI solutions.
Embed AI into operational workflows, internal systems, and business applications.
Embed AI into operational workflows, internal systems, and business applications.
Build customer facing tools, applications, and AI-powered platforms.
Support software development, debugging, code generation, and engineering workflows.
Llama stands out for its flexibility and customisation options, allowing organisations to build, fine-tune, and deploy AI within their own environments rather than relying entirely on closed AI platforms.
Common use cases include AI assistants, workflow automation, coding support, enterprise search, content generation, research, and customised AI applications built around internal systems and data.
Yes. Llama can integrate with APIs, enterprise platforms, cloud environments, and other AI systems.
Yes. Llama can be deployed within private cloud, enterprise, or on-premise environments depending on business and security requirements.
Yes. Llama is widely used by developers and technical teams because it supports fine-tuning, custom integrations, and flexible AI application.
