AI Application Developer

Pranjal .

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Starting at

About this service

Summary

You'll be getting an AI application customized for your specific use cases, whether it's customer care, FAQs, or more. It can be easily integrated with almost any of your existing platforms, such as Discord, Slack, Telegram, and others.

Process

Planning and Requirements

Identify use cases (e.g., customer care, FAQs).

Define goals and success metrics.

Gather user requirements.

Technology Selection

Choose base LLM.

Select embedding service (e.g., Cohere).

Decide on a cloud provider (e.g., MS Azure).

Data Preparation

Collect and clean training data.

Annotate data if necessary.

Model Training and Integration

Fine-tune the LLM with domain-specific data.

Implement RAG for enhanced information retrieval.

Development

Develop backend infrastructure.

Create REST API endpoints.

Ensure integration with platforms like Discord, Slack, Telegram.

Testing and Deployment

Conduct unit and integration testing.

Deploy on the chosen cloud provider.

Set up for scalability.

Monitoring and Maintenance

Monitor performance and update regularly.

Provide user support and address feedback.

What's included

A customized LLM powered chatbot.
A customized LLM-powered chatbot, enhanced with Retrieval-Augmented Generation (RAG) and fine-tuning, offers advanced natural language understanding and contextual awareness. RAG enables dynamic and accurate responses by retrieving relevant information, while fine-tuning tailors the chatbot to specific domains for improved accuracy and relevance. This combination ensures precise, contextually appropriate interactions, enhancing user experience and providing robust, domain-specific assistance.
REST API endpoints of your bot.
REST API endpoints for your bot provide standardized interfaces for interaction. They allow external applications to communicate with the bot, sending and receiving data through HTTP requests. Key endpoints include those for initiating conversations, sending messages, retrieving responses, managing user sessions, and accessing bot settings. These endpoints facilitate seamless integration, ensuring that the bot can be easily accessed and utilized across various platforms and applications.

Example projects