Modules

Deployment

Train with External Sources

Integration with external enterprise systems like CRM (Customer Relationship Management), ERP (Enterprise Resource Planning), and databases enhances the chatbot's functionality. This allows it to fetch real-time customer details, update records, and assist users with personalized responses, making it an effective tool for business automation.

Support Multiple Rounds

Effective chatbot interactions go beyond simple one-question-one-answer exchanges. Multiple-round conversation engine support allows the chatbot to maintain context across several exchanges, enabling a more natural and human-like interaction. This feature helps in handling complex queries where follow-up questions are needed for clarity before providing a final response.

Self-Expand Knowledge Base

A modern chatbot can dynamically expand its knowledge base by learning from past conversations, FAQs, and structured data sources. Through machine learning and natural language processing (NLP), it can refine its responses, recognize new patterns, and improve its understanding over time, reducing the need for manual updates.

Dedicated Domain Library

Ensures it understands industry-specific terminology and use cases. Whether it is used in healthcare, finance, or customer support, the chatbot leverages predefined datasets and expert knowledge bases to provide accurate and context-aware responses. This makes interactions more relevant and efficient for users within a specific field.

Support Multiple Platforms

A chatbot should be accessible across various communication channels, including web, mobile apps, messaging services (WhatsApp, Slack, Microsoft Teams), and voice assistants (Alexa, Google Assistant). This ensures users can engage with the chatbot through their preferred platform, improving accessibility and user experience.

Allow API Connection

The chatbot can interact with third-party services and applications. This capability enables advanced functions like retrieving order statuses, processing transactions, booking appointments, or automating workflows. API connectivity enhances the chatbot’s usability, making it a valuable tool for business operations.

Modules

Deployments

Real-Time Monitoring and Updates

A chatbot's performance needs continuous improvement. With real-time monitoring and updating, administrators can track interactions, analyze key metrics, and fine-tune responses dynamically. This ensures the chatbot remains accurate, responsive, and aligned with user expectations, leading to a better overall experience.

Support Fine Tune LLM

Fine-tuned popular LLMs, such as Anthropic and Meta's open-source models, can be adjusted and provide data for further training as needed. The trained model can also run on an on-site GPU units.