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GnanaPrakash Balakrishnan

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Co-Founder & CEO of Maticz, brings vast experience in blockchain, AI, and product engineering. With strong leadership in building scalable digital solutions, Gnanaprakash drives innovation and growth across global Web3 and enterprise technology projects.

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FAQ

FAQ

Connect with our experts for detailed technical consultation.

FAQ

Yes. Maticz builds custom large language models (LLMs) from the ground up, tailored to your business goals and domain. Our approach starts with understanding your workflows, expected outcomes, and more. From there, we handle everything in the complete development process. This approach ensures that your LLM aligns precisely with your operations rather than forcing your business to adapt to a generic LLM model.

Maticz follows a structured, data-secure approach to train LLMs, which ensures the model delivers accurate and context-aware responses. We begin with data assessment and preparation, where we analyze your structured and unstructured data. And based on your goals, we then choose the right strategy, such as fine-tuning, retrieval-augmented generation (RAG), or hybrid training. This combination improves accuracy while keeping costs and retraining cycles low.

Our experts will help reduce hallucinations in LLM responses by combining controlled data grounding and model tuning to ensure that the output remains accurate. At first, we ground the model in verified data using RAG to reduce the chances of fabricated or outdated information. Next, we apply domain-specific fine-tuning to teach the model how to respond, this will ensure the LLM delivers trustworthy responses.

The timeline to develop a custom LLM depends on the complexity of your project.  On average, a custom LLM project takes 8 to 16 weeks from initial discovery to production deployment. At Maticz, we follow an agile, milestone-driven process for faster delivery without compromising accuracy, security, or any kind of standards to make your LLM model be set as a benchmark.

Maticz delivers business-ready LLM solutions focused on real operational outcomes, not just model building. We provide end-to-end LLM development that helps you choose the right approach, from custom models to fine-tuning or RAG, backed by continuous optimization and long-term support.

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