Google Gemini
generalGoogle's multimodal AI with long-context processing and built-in Search grounding
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.
Google's multimodal AI with long-context processing and built-in Search grounding
Calendar automation for tasks, habits, and breaks
Secure, scalable AI agents for customer conversations
Cold email and lead generation tool
Omnichannel customer support automation
AI phone and SMS platform for sales and support
Small language model platform for edge computing
Automatic meeting summaries and notes
24/7 AI emotional support designed for female health
Audio conversations with historical figures and modern coaches
Use ChatGPT on WhatsApp for chat, images, and documents
Shopify chatbot for customer support
Interview preparation using the STAR method
Connect with departed loved ones through AI
Chat with multiple AI models and install custom assistants
Performance marketing and ad optimization
Query your codebase using plain language
AI-driven career planning and skill development
Interview analysis and candidate assessment
Automate customer support responses and FAQ handling
Practice interviews with real scenarios
AI chatbot with conversation memory
Local AI chat on iPhone, iPad, and Mac
Build custom algorithms for data and AI solutions
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.