Our Full-stack AI platform, designed with both hardware and software solutions, is built to provide seamless integration, offering a comprehensive stack ready for deployment on-premise or in the cloud. From powerful Nvidia GPUs and cloud-ready hardware, to intelligent orchestration tools and advanced AI models, IG1’s stack ensures efficient and scalable Gen AI implementations. We offer flexible configurations tailored to your needs, enabling rapid deployment and immediate productivity with your AI-driven initiatives.
Unlock the full potential of AI with our multi-layer stack, seamlessly integrating hardware, model services, orchestration, and LLM capabilities. From infrastructure to deployment and management, we provide a complete solution for powering your AI-driven innovations.
Harness the full potential of your AI solutions with our comprehensive, multi-layered platform. Seamlessly integrating cutting-edge hardware, advanced model services, and full AI orchestration, we provide end-to-end support—from infrastructure deployment to model fine-tuning and management— empowering you to accelerate innovation and stay ahead of the competition.
Hardware & cloud infrastructure form the foundational layer of the Generative AI stack, providing the necessary computational power and flexibility for training and deploying AI models.
Iguana Solutions offers top-tier, on-premise infrastructure with expert deployment and AI-optimized hardware, providing complete control, reliability, and superior performance for your AI-driven operations.
At the heart of any AI-driven solution lies the robustness and reliability of the hardware infrastructure. Iguana Solutions provides top-tier, on-premise infrastructure solutions, ensuring your data is in trusted hands from start to finish.
Our team of experts meticulously handles every stage of hardware deployment, from unpacking and racking servers to connecting power and networking. With NVidia GPUs and top-of-the-line servers, our infrastructure is designed to meet the highest performance demands.
Our team of experts meticulously handles every stage of hardware deployment, from unpacking and racking servers to connecting power and networking. With NVidia GPUs and top-of-the-line servers, our infrastructure is designed to meet the highest performance demands.
Our infrastructure is purpose-built to drive AI workloads, leveraging the power of NVidia GPUs for superior computational acceleration.
We offer end-to-end management of cloud infrastructure, carefully designed and deployed to meet the specific requirements of your Full-Stack AI Platform. We ensure that the cloud environment seamlessly supports all layers of your AI operations
We provide more than just hardware. We assist you in every phase, from designing your server infrastructure to ensuring a seamless installation process, customized for your Full-Stack AI Platform needs.
OS: IG1 AI OS, a specially designed operating system tailored for AI services, leveraging our deep expertise and capability in managing “plug and play” platforms for AI.
Latest NVidia drivers for the GPUs.
”CUDA toolkit” is embedded in IG1 OS.
KUBE by IG1 provides a cutting-edge platform designed to manage AI workloads through virtualization and containerization. It is specifically optimized for handling intensive AI computations, offering seamless integration with the latest GPUs and TPUs. This ensures accelerated model training, efficient resource management, and enhanced AI performance.
The KUBE Cluster is built to support high-performance AI applications, leveraging Kubernetes’ advanced scheduling and scaling features. With native integration for AI-specific hardware, the cluster efficiently handles containerized applications, ensuring optimal resource utilization for AI processes.
KUBE by IG1 includes built-in health monitoring to ensure that all components are functioning at their peak. This helps maintain consistent performance, identifying potential issues early to avoid disruptions in AI workflows.
AI applications rely on generative models, such as LLAMA3, Mistral, Deepseek, and StarCoder, which are pre-trained models on vast datasets to capture complex patterns and knowledge. These models serve as building blocks for various AI tasks, including natural language processing and image generation. To effectively deploy and manage AI applications, several services are needed to ensure the proper functioning of Large Language Models (LLMs). These services include quantization for resource optimization, inference servers for model execution, API core for load balancing, and observability for data collection and trace management. By fine-tuning and optimizing these models on specific datasets, their performance and accuracy can be enhanced for specialized tasks. This foundational step enables developers to leverage sophisticated models, reducing the time and resources required to build AI applications from scratch.
Download the LLM (Large Language Model) and perform quantization to optimize performance and reduce resource usage. This step ensures the AI model runs efficiently and is ready for integration with other components.
Integrate RAG components using the most used framework and deploy the RAG pipeline within KUBE. This step enhances the AI model with retrieval-augmented capabilities, providing more accurate and relevant responses.
Integrate AI-powered image generation components, such as ComfyUI, to deploy image generation pipelines. This step enables the creation of high-quality images from text inputs or other sources, providing a complete visual generation system within your AI framework.
Obtain the LLM from the appropriate source. Purpose: Provides the base AI model for various applications.
Optimization involves enhancing and preparing LLMs for efficient resource usage through quantization. This process significantly boosts inference performance without compromising accuracy. Our quantization management services use the AWQ project, known for delivering exceptional speed and precision
Like database engines, inference servers load models and execute requests on GPU. IG1 installs and manages all the necessary services for the proper functioning of LLM models. To ensure optimal performance, we rely on several instances:
Set up the necessary RAG components (example using the LlamaIndex framework):
Deploy the RAG pipeline within the KUBE environment.
Obtain the Image Generation Model from the designated source, such as Flux Dev or Stable Diffusion.
Construct a custom Docker image by integrating ComfyUI, a node-based interface to create image generation pipelines, which serves as an inference server for image model.
Implement a pre-designed workflow that is specifically optimized for the chosen image generation model;, for instance: Flux Dev.
Support Configure the chat interface, to enable image generation capabilities through ComfyUI.
This Layer is about the critical processes of integrating, orchestrating, and deploying AI infrastructure to ensure seamless and efficient operations. As AI applications become increasingly complex and integral to business operations, it is essential to have a robust framework that supports the integration of various services, the orchestration of containerized applications, and the deployment of these applications with minimal friction.
By leveraging advanced tooling and best practices, organizations can achieve greater scalability, reliability, and performance for their AI systems. We will explore the key components and strategies required to build a resilient and scalable AI infrastructure that meets the evolving needs of modern enterprises.
Integrate various AI services seamlessly to ensure efficient communication and operation. This includes:
The API Core acts as a Proxy LLM, balancing the load between LLMs inference server instances. LiteLLM, deployed in High Availability, is used for this purpose. It offers wide support for LLM servers, robustness, and usage information and API key storage through PostgreSQL. LiteLLM also enables synchronization between different instances and sends LLM usage information to our observability tools.
Implement observability tools to gain insights into the behavior and performance of your AI applications:
The LLMs observability layer collects usage data and execution traces, ensuring proper LLM management. IG1 efficiently manages LLM usage through a monitoring stack connected to the LLM orchestrator. Lago and OpenMeter collect information, which is then transmitted to our central observability system, Sismology.
It represents the tangible end-user implementations of generative models, demonstrating their practical value. These applications, such as text, code, image, and video generation tools, leverage advanced AI to automate tasks, enhance productivity, and drive innovation across various domains. By showcasing real-world uses of AI, this section highlights how generative models can solve specific problems, streamline workflows, and create new opportunities. Without this layer, the benefits of advanced AI would remain theoretical, and users would not experience the transformative impact of these technologies in their daily lives.
Set up the Hugging Face web interface for model management and prompting.
Set up an API server to provide programmatic access to the LLM and RAG services.
Implement a user interface for interacting with the RAG system.
Set up an API server to provide programmatic access to the LLM and RAG services.
Install a low code tool for building LLM-based applications.
A graph-based interface to design and execute image generation pipelines
Explore GenAI’s impact on professional services: from LLMs’ pros and cons to RAG’s benefits, challenges, and improvements, and its application at Iguana Solutions.
“ With our previous partner, our ability to grow had come to a halt.. Opting for Iguana Solutions allowed us to multiply our overall performance by at least 4. “
Cyril Janssens
CTO, easybourse
We offer innovative Gen AI platforms that make AI infrastructure effortless and powerful. Harnessing NVIDIA’s H100 and H200 GPUs, our solutions deliver top-tier performance for your AI needs. Our platforms adapt seamlessly, scaling from small projects to extensive AI applications, providing flexible and reliable hosting. From custom design to deployment and ongoing support, we ensure smooth operation every step of the way. In today’s fast-paced AI world, a robust infrastructure is key. At Iguana Solutions, we’re not just providing technology; we’re your partner in unlocking the full potential of your AI initiatives. Explore how our Gen AI platforms can empower your organization to excel in the rapidly evolving realm of artificial intelligence.
We offer innovative Gen AI platforms that make AI infrastructure effortless and powerful. Harnessing NVIDIA’s H100 and H200 GPUs, our solutions deliver top-tier performance for your AI needs. Our platforms adapt seamlessly, scaling from small projects to extensive AI applications, providing flexible and reliable hosting. From custom design to deployment and ongoing support, we ensure smooth operation every step of the way. In today’s fast-paced AI world, a robust infrastructure is key. At Iguana Solutions, we’re not just providing technology; we’re your partner in unlocking the full potential of your AI initiatives. Explore how our Gen AI platforms can empower your organization to excel in the rapidly evolving realm of artificial intelligence.
Embark on your DevOps journey with Iguana Solutions and experience a transformation that aligns with the highest standards of efficiency and innovation. Our expert team is ready to guide you through every step, from initial consultation to full implementation. Whether you’re looking to refine your current processes or build a new DevOps environment from scratch, we have the expertise and tools to make it happen. Contact us today to schedule your free initial consultation or to learn more about how our tailored DevOps solutions can benefit your organization. Let us help you unlock new levels of performance and agility. Don’t wait—take the first step towards a more dynamic and responsive IT infrastructure now.
