Maximize AI Performance with Custom LLM Finetuning Services

Our custom Large Language Model finetuning will enhance your AI model's accuracy and relevancy in your domain. Get continuous support to ensure your AI remains cutting-edge.

Fine-tune your AI models to be razor sharp

Custom AI LLM Fine-Tuning

Large Language Model fine-tuning services to optimize AI models you use for specific industries, use cases, and contexts.

On-Premise LLM Consulting

For companies that handle sensitive data, we provide on-premise LLM fine-tuning consultancy to ensure maximum security and privacy.

Continuous Model Update and Maintenance

We offer continuous services to ensure your AI models stay relevant, accurate, and efficient over time.

Bespoke LLM finetuning for AI businesses


Make perfectly tuned LLM models benefit your business

Our fine-tuned LLMs result in higher quality results than prompt engineering alone, cost savings through shorter prompts, the ability to reach equivalent accuracy with a smaller model, lower latency at inference time, and the chance to show an LLM more examples than can fit in a single context window.

AI usability starts with a finely-tuned LLM

AI usability starts with a finely-tuned LLM

Customer service chatbots

LLM fine-tuning for customer service chatbots. Improved user interaction and productivity.

Legal document processing

Fine-tuning LLM for legal briefs, contracts, and other legal documents. Accurate, efficient processing of legal documents.

Financial document processing

LLM fine-tuning for financial reports, invoices, and receipts. Cost savings through shorter prompts, higher-quality results.

Medical report processing

Fine-tuning LLM for medical prescriptions, reports, and documents. Accurate, efficient processing of medical documents.

Content generation

Fine-tuning LLM for content generation. Improved language understanding and generation.

Industry-specific language

LLM fine-tuning for industry-specific language and contexts. More accurate and relevant results.

AI technologies we work with


OpenAI's large language model frequently employed for human-like text generation, conversation simulation, and data analysis.


PyTorch is a machine learning platform grounded on the Torch library, frequently utilized for tasks including computer vision and natural language processing.


Generative AI used to create realistic images from natural language descriptions.

See some examples of our work

Trust Stamp

TrustStamp, a leading provider of AI-powered identity solutions, partnered with 10Clouds to overcome development and staffing challenges and achieved remarkable success.

10Clouds helped developed TrustStamp's state of the art proof of liveliness solution for KYC and computer vision tools for document verification.

This collaboration led to full-scale implementation, adoption by strategic partners, and TrustStamp's debut on NASDAQ.

The partnership exemplifies the power of collaboration and innovation, solidifying TrustStamp's position as a trusted identity solution provider.

Trust Stamp case study image


AIConsole is an AI-powered personal assistant designed to tackle a broad range of tasks. With its help you can generate content, code and visuals, get work management assistance and easily fetch data.

case study image

10Clouds AI Assistant

We have developed a powerful tool that can collect data from company handbooks, employee information, project details, and more to provide instant feedback.

The process of creating this tool involved several stages, such as downloading data from the Confluence API and saving it to a PostgreSQL database. Next, we cleared the data of HTML tags and added it to Pinecone using Llama-index, a library for importing data.

Our AI tool can quickly and accurately provide users with the information they need, making it an invaluable asset for any organization.

10Clouds AI Assistant case study image


What is LLM fine-tuning?


LLM fine-tuning is the process of training a language model on specific examples of prompts and desired responses to improve its performance and relevance in a particular domain.

What are the benefits of LLM fine-tuning?


LLM fine-tuning can lead to higher quality results than prompt engineering alone, cost savings through shorter prompts, the ability to reach equivalent accuracy with a smaller model, lower latency at inference time, and the ability to show an LLM more examples than can fit in a single context window.

What kind of data is needed for LLM fine-tuning?


The training data for LLM fine-tuning should consist of prompt and response pairs. Having high-quality data is essential to improving performance.

What is included in 10Clouds' LLM fine-tuning services?


Our LLM fine-tuning services include custom LLM fine-tuning, application-specific training, maintaining ethical use of the models, on-premise training, regular model updates and maintenance, and training and consultation services.

How is the quality of the fine-tuned model affected by the size of the dataset?


As a rule of thumb, you should expect to see linear improvements in your fine-tuned model's quality with each doubling of the dataset size. For every linear increase in the error rate in your training data, you may encounter a roughly quadratic increase in your fine-tuned model's error rate.

Does 10Clouds offer technical support for its LLM fine-tuning services?


Yes, we offer technical support to solve any issues our clients may encounter.

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