Conversational AI has emerged as a transformative technology for businesses seeking to enhance customer engagement, streamline operations, harness AI innovation, and gain a competitive edge. However, with a growing number of vendors and platforms offering conversational AI solutions, selecting the right one can be a daunting task.
AI presents a nearly endless array of benefits to enterprises, but at boost.ai we excel in eight unique areas. There are many more comparison points to be made across competitive alternatives, but we believe these eight reasons help us stand out in the ever-expanding market of enterprise AI.
Following are the eight key capabilities that have made boost.ai a best-in-class conversational AI solution and a top choice for enterprises looking to gain the benefits of conversational AI:
1. Topic Switching: Seamless Transitions Within Conversations
One of the most challenging aspects of conversational AI is handling topic switching within the same conversation. Customers often jump from one topic to another, and a robust platform must adapt without losing context or providing irrelevant responses.
Although some solutions enable a user to switch topics by going back to a static drop-down menu, boost.ai enables customers to seamlessly switch between topics without having to restart the conversation in its entirety. Seamless transitions are achieved through advanced natural language understanding (NLU) and contextual memory, which enables the system to track the conversation’s flow and adjust accordingly. This is why, with a boost.ai agent, users won’t see "What else can I help you with" followed by a preselected menu.
2. Generative Context: Switching Between Generative and Conversational Flows
Modern conversational AI platforms must balance predefined conversational flows with generative AI capabilities. The ability to switch mid-conversation between these modes while maintaining context is crucial for delivering accurate and relevant responses.
Many solutions create a noticeable pause when switching between models, causing customers to experience a disjointed flow between their engagement with predefined and generative conversations. Unlike those solutions, boost.ai delivers a truly seamless experience. When talking with a boost.ai AI agent, customers are never able to tell whether the model providing a response is predefined or generative,
3. Knowledge Updates: Automatic and Scheduled Updates
The modern enterprise needs to remain agile, especially when operating at scale. A customer's experience can change on a daily basis, given product updates or special promotions. When new information is available, it's crucial for enterprises to have a simple method of updating their AI agent, just like they would a human.
Manual updates can be time-consuming and prone to errors, making automation a productivity improving capability for any conversational AI platform. boost.ai automatically updates its knowledge sources on a fixed schedule, such as daily or weekly. This ensures that the system always has access to the latest information without requiring manual intervention. The platform integrates seamlessly with external databases, CRMs, and knowledge management systems, enabling real-time updates and synchronization.
4. Custom Guardrails: Unique Rules for Individual Topics
Guardrails are critical for preventing harmful or offensive outputs, ensuring compliance, and maintaining reliability and relevance. Guardrails can prevent AI system hallucinations and keep responses accurate and contextually appropriate. Guardrails use rules, filters, and monitoring mechanisms to ensure tat AI systems operate within predefined ethical, legal, and operational bounds.
boost.ai enables businesses to apply unique guardrails to individual topics. The platform provides granular control over guardrails, enabling businesses to define specific rules based on intent, context, or user type. Guardrails can be dynamically adjusted based on real-time feedback and performance metrics, ensuring continuous improvement and compliance. Boost.ai guardrails also can be managed in a centralized location, giving AI managers a simple interface to present total visibility into their AI agent's guardrails.
5. Guardrail Triggers: Measuring User Input and Large Language Model (LLM) Responses
Effective guardrails monitor user inputs and AI LLM responses to ensure compliance and accuracy. This dual focus helps prevent inappropriate or off-topic interactions.
boost.ai guardrails measure user input and LLM responses before triggering. This ensures that the system remains aligned with business goals and user expectations. The platform can proactively alert human agents when a conversation risks violating guardrails, enabling timely intervention. Businesses can customize guardrail triggers based on specific criteria, such as sentiment, intent, or compliance requirements.
6. Fine-Tuning Proprietary Datasets for Enhanced Performance
The ability to fine-tune LLMs with proprietary datasets is critical for achieving optimal performance in specific use cases. This ensures that the models are optimized for particular industries, languages, and use cases.
boost.ai fine-tunes its LLMs using proprietary datasets tailored to the needs of its clients, including solutions customized for FinServ, insurance, telecom, public sector organizations. The boost.ai platform also supports continuous learning, enabling the models to improve over time based on real-world interactions and feedback. Fine tuning not only yields a better user experience, it enables boost.ai to deliver industry-leading time-to-value.
7. Conversation Review: Automated Analysis and Labeling
Reviewing and analyzing conversations is essential for improving AI performance and identifying areas for enhancement. Manual reviews are time-consuming and inconsistent, whereas automating this process can save time and provide actionable insights.
The boost.ai platform provides AI-powered CX Insights that enable automatic review of every single conversation a virtual agent has with customers, giving enterprises detailed, actionable insights. This level of transparency increases an organization’s ability to execute data-driven changes in their customer experience and react to emerging trends and customer issues in real time.
8. Custom Masking: Advanced Data Protection
Data protection is a top priority for businesses, especially when handling sensitive information. Custom masking ensures that sensitive data is anonymized or redacted as needed.
boost.ai enables businesses to define custom data types and entity models, enabling businesses to create tailored solutions for data protection. Sensitive data is masked in real-time during conversations, ensuring compliance with data protection regulations and safeguarding user privacy.
Conclusion: 8 Big Reasons Why Boost.ai Is the Leader in Conversational AI
The eight ways in which boost.ai excels in adapting to complex conversational dynamics, integrating with existing systems, securing data, and delivering personalized interactions make it a standout choice for enterprises across industries. As conversational AI continues to evolve, boost.ai is setting the standard in delivering the most robust, flexible, and secure conversational AI platform. Whether you’re looking to enhance customer support, streamline operations, or protect sensitive data, boost.ai provides the most capable conversational AI solution to meet your needs.
