Whether you’re building on open-source foundations, proprietary APIs, or hybrid stacks, we can help improve your agent. Our domain specialists and data teams adapt the training pipeline to suit each model’s strengths and deployment requirements.
LLaMA
Meta’s LLaMA (Large Language Model Meta AI) models are highly efficient and optimized for fine-tuning across diverse tasks. With variants like LLaMA 2 and the upcoming LLaMA 3, they offer strong performance and are especially suitable for on-premise deployments, data-sensitive environments, and use cases requiring full model control. We help businesses customize and deploy LLaMA-based models with security, compliance, and scalability in mind.
GPT (OpenAI)
GPT models are the most well-known LLMs and are commonly accessed through OpenAI’s API or via platforms like Azure OpenAI. They excel at general-purpose tasks and integrate well with customer support agents, content creation, and complex reasoning workflows. Our team supports both prompt-based optimization and embedding-based retrieval augmentation, as well as supervised fine-tuning on internal knowledge bases when available.
Falcon
Developed by the Technology Innovation Institute (TII), Falcon models are powerful open-source alternatives designed for cost-efficient inference and scalable fine-tuning. They fit the public sector, academic research, and any application that benefits from open governance and transparency. We assist teams in training and deploying Falcon models in production-grade pipelines with human-in-the-loop QA.
Mistral
Mistral’s models (like Mistral 7B and Mixtral) are lightweight, high-performance open-source LLMs that excel in edge computing and low-latency inference. These models are ideal for businesses that need flexible, fast models with strong multitask capabilities. Our fine-tuning services make them even more efficient and context-aware for niche domains - especially where GPU constraints or response speed are critical.
Claude (Anthropic)
Claude, developed by Anthropic, is designed with a strong emphasis on harmlessness, honesty, and helpfulness—making it a powerful choice for applications where alignment and ethical safety are critical. It’s widely used in enterprise chatbots, knowledge management, and moderation tasks, especially when natural, conversational tone and safety guarantees are a priority. We support organizations in tailoring Claude’s behavior through structured prompt strategies, fine-tuning via APIs, and human-in-the-loop validation for compliance-heavy industries.
Open Source LLMs
We also work with a wide range of other open-source models including Vicuna, Zephyr, OpenChat, and Instruct-tuned derivatives. These are often used in experimental applications, sandbox environments, or for organizations building fully self-hosted AI infrastructure. Our pipeline allows for training, validation, and deployment of these models with full human feedback integration, ensuring their outputs meet enterprise-grade quality.
