LLM custom development

Build a customized LLM specific to the business need 

A21.ai helps its clients with Customized Large Language Models needed for tailored accuracy, control over training data, unique features, and performance optimization specific to business needs

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LLMs for Automation and Innovation

  • Custom train & develop LLMs for domain-specific needs using Reinforcement Learning with Human Feedback (RLHF)
  • Solve business problems in different domains with LLMs using frameworks such as LangChain
  • Scale generative AI applications with LLMOps
  • Design custom prompts to generate creative and informative text
  • Ensure the safety, quality, and structure of LLM responses using GuardRails
  • Automate enterprise processes, such as customer experience, contact centers, report generation, and others, and infrastructure with LLMs

a21.ai Methodology

Develop App Blueprint

We collaborate closely with our clients to gain a deep understanding of their specific business requirements, challenges, and objectives.

This includes identifying the tasks, processes, or areas where generative AI can bring value and enhance efficiency.

Model Selection

Based on the identified needs, we select the most suitable pre-trained generative AI model or a combination of models.

This could range from popular models like GPT-3, GPT-4, or specialized image-based generative models or combination of a number of large and small language and vision models

Data Integration

We integrate the client’s data sources, whether text, images, or other forms of data, into the generative AI system.

This can be achieved through seamless data import from various sources such as databases, cloud storage, APIs, or real-time data streams.


LLM Customization

Step 1: Model Training: Adjusting the architecture and training the model using these datasets, potentially iterating to refine accuracy and relevance.

Step 2: Model Fine-Tuning: Applying additional training on smaller, more specialized datasets to refine the model’s performance for specific tasks or industries


Testing & Evaluation

Before full deployment, thorough testing and evaluation of the integrated generative AI system are conducted.

This ensures its performance, accuracy, and compatibility with the client’s workflows, as well as the generation of high-quality outputs.

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Workflow Integration

Our team collaborates with the client’s IT and development teams to integrate the generative AI solution into their existing workflows and systems.

This includes developing APIs, connectors, or custom interfaces to enable smooth communication and interaction between the generative AI system and other tools or applications used by the client.

 

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Deploy & Monitor

Once the Generative AI system is tested and approved, it is deployed into the client’s production environment.

Continuous monitoring and performance evaluation are carried out to ensure optimal functioning, reliability, and scalability of the solution.

Support & Maintenance

We provide ongoing support, maintenance, and updates to the generative AI integration, ensuring it remains up-to-date, efficient, and aligned with any changing business requirements or technological advancements.


 

Get Started With AI Experts

Write to us to explore how LLM can be customized for the unique needs of the business.