Fin by Intercom
supportAI support agent built into the Intercom helpdesk
AI chat tools include chatbots, conversational assistants, and platforms for building and deploying chat-based AI experiences. With 955 tools, this is one of the largest categories in the directory, covering everything from customer service bots to personal AI companions and sales coaching systems.
AI support agent built into the Intercom helpdesk
AI productivity suite for email and work
Documentation platform with AI-powered Q&A
Free AI chatbot powered by ChatGPT 4
AI agents for customer support in 80+ languages
Amazon seller tools with data insights for e-commerce growth
AI companion for personalized conversation
CRM and rolodex for personal and professional relationships
Custom AI character and companion with chat and voice
Free AI friend for chat and reflection
Customer feedback and survey tool
AI app for Quran memorization and learning
Frontend framework for LLM and agent integration
Unified inbox for Shopify customer support
Platform for system design and behavioral interview prep
AI platform that protects learning in education
Extract email addresses from LinkedIn profiles
Personalized chatbot trained on your website
AI-powered short links for team information sharing
Summarize, search, and write using multiple AI models
Custom multilingual AI assistants for customer service
AI interview coaching and practice
Interactive lessons aligned to school curriculum
AI email management and prioritization
The breadth here is significant. On one end are end-user chat applications where you interact with an AI directly, like CogBias AI or Eloquens AI. On the other are platforms like Markprompt that let you build custom chat interfaces on top of your own documentation or knowledge base. Sales-specific tools like Salesably and Triple Session focus on coaching and call analysis rather than open-ended conversation. Customer support tools like Watchdog.chat and AIPEX are deployed externally, handling queries on behalf of a business. When evaluating, the key question is whether you need a ready-made chat product or infrastructure to build your own. For the latter, the quality of the RAG pipeline, latency, and customization options matter most. For end-user products, context retention across sessions and instruction-following quality are the main differentiators. Pricing varies from free tiers to per-conversation billing.