Parloa

Automatically detects customer language and conducts conversations in 80+ languages without requiring separate chatbot instances per language. Maintains conversation context and intent recognition across language switches.

Routes and manages customer conversations across multiple communication channels (web chat, WhatsApp, Telegram, phone) from a single unified backend. Maintains conversation history and context regardless of channel switching.

Builds and maintains customer profiles by collecting information across conversations, integrating with CRM data, and tracking customer history and preferences.

Analyzes customer sentiment and emotional tone in messages to detect frustration, satisfaction, or urgency. Triggers appropriate responses or escalations based on detected sentiment.

Maintains comprehensive logs of all conversations for compliance, audit, and quality assurance purposes. Supports data retention policies and regulatory requirements.

Allows training of custom NLP models on domain-specific language and terminology to improve intent recognition and entity extraction accuracy for specialized industries.

Enables non-technical users to build complex conversation flows and dialogue trees using a visual interface without writing code. Supports conditional logic, branching, and dynamic responses.

Uses advanced NLU to understand customer intent from messages, maintain conversation context across multiple turns, and handle complex multi-step customer service scenarios. Distinguishes between similar intents and understands nuanced language.

Translates customer messages and bot responses in real-time across 80+ languages while preserving intent, tone, and context. Enables agents and bots to communicate seamlessly across language barriers.

Connects chatbot conversations to existing business systems (CRM, databases, APIs) to access customer data, retrieve information, and execute transactions. Enables bots to perform actions beyond conversation.

Tracks and analyzes chatbot performance metrics including conversation volume, resolution rates, customer satisfaction, and common issues. Provides dashboards and reports for optimization.

Seamlessly transfers conversations from chatbot to human agents when needed, preserving full conversation context and customer information. Manages queue, routing, and escalation logic.

Identifies and extracts specific information entities from customer messages (names, dates, order numbers, product names, etc.) to populate forms, trigger actions, or enrich customer profiles.

Allows creation of multiple versions of conversation flows, A/B testing different dialogue approaches, and safe deployment of changes without affecting live conversations.