We've deployed chatbots with enterprises for years. Here are the most common mistakes we see.
AI document indexing helps you turn unstructured files into searchable knowledge, enabling semantic search for RAG.
Website chatbots simplify customer service and support workflows. They also help support teams access customers' conversation history for optimized support.
AI in e-commerce is used to personalize online shopping experiences and offer 24/7 support. Companies also use it to forecast demand, and improve safety.
AI agents automate workflows, perform data analysis, and make decisions autonomously, saving companies up to $300M in overhead costs.
Building a react chatbot can be done in a few lines of code using simple chatbot and the Botpress client library.
AI hallucination is when AI relays false information. It's caused by poor data and prompting, but platforms implement safeguards to keep it from affecting users.
Conversation design involves decision making, natural language processing, and recovery paths to balance a structured flow with a fluid feel.
AIOps leverages AI for IT operations like correlating events and detecting anomalizes. It's best used with centralized data in well-structured pipelines.
Machine learning is used in marketing for analytics, churn prediction, and dynamic pricing. It can be done with tools like Botpress, Mailchimp, and Hubspot.
Intelligent Process Automation (IPA) let businesses automate the processing of unstructured inputs in processes like document parsing and ticket routing.
SMS chatbots are chatbots connected to SMS through service providers. They boast a higher open rate than email.
Chatbots are most successful when they define clear KPIs, keep conversations clear, and benefit technical and non-technical teams.