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AI super-assistant plus enterprise ML platform: ChatLLM for teams and end-to-end model building for enterprises; broad, pricing not shown.
AI assistant for teams with secure LLM and company-knowledge access.
Subscription bundle of a dozen role-based AI assistants (support, social, sales, SEO, and more) letting small teams delegate routine work.
Enterprise platform for designing, launching, and scaling AI agents across voice and chat customer experience channels.
Open-source platform to build, deploy and monitor agentic AI workflows and RAG apps, with cloud, self-host and enterprise options.
No public pricing
No public pricing
No public pricing
Free trial available
- ✦ChatLLM access to multiple top AI models
- ✦AI agents and automation
- ✦No-code full-stack app creation
- ✦Enterprise generative AI platform
- ✦Structured ML model building
- ✦Optimization and forecasting
- ✦Unified and safe access to GPT-4
- ✦Connection to team's data for up-to-date answers
- ✦Customizable AI agent building without code
- ✦Team collaboration features for sharing prompts and conversations
- ✦Suggestions for documentation updates and improvements
- ✦12+ role-specific AI helpers covering support, sales, SEO, and more
- ✦One-click use-case templates for common tasks
- ✦15+ third-party integrations
- ✦Custom brand knowledge base ('Brain AI')
- ✦Support for 100+ languages
- ✦Continuous 24/7 automated operation
- ✦No-code, chat-based interface
- ✦Visual workflow builder for conversational AI agents
- ✦Support for multiple LLM providers or bring-your-own-model
- ✦Deployment across voice and chat channels
- ✦Real-time observability and performance analytics
- ✦Team collaboration with roles and permissions
- ✦API integrations with existing business tools
- ✦Visual workflow studio for agents
- ✦RAG knowledge pipelines
- ✦Agent runtime with tools and memory
- ✦Marketplace of models and plugins
- ✦Publish as app, API or MCP tool
- ✦Logging, analytics and monitoring
- →Chat with many AI models in one place
- →Build and deploy ML models
- →Automate tasks with AI agents
- →RevOps & Sales: Create customer profiles, flag at-risk deals, analyze calls, generate SQL.
- →PMM & Marketing: Write on-brand content, create consistent messaging, translate content, extract insights.
- →Customer Support: Connect to knowledge base, identify product improvements, auto-create FAQs, provide real-time guidance.
- →Product & Design: Improve product copy, analyze customer sentiment, extract competitor insights, generate user stories.
- →Engineering: Review code, auto-create docs, compile incident timelines, generate SQL.
- →Data & Analytics: Enable non-technical teams to query data, automate reporting, transform insights, connect data sources.
- →Automating social media scheduling and content creation
- →Handling routine customer support replies
- →Drafting marketing copy and email campaigns
- →Turning business data into actionable insights
- →Running SEO audits and optimizing content
- →Screening candidates and drafting recruiting materials
- →Support teams automating customer service chatbots
- →Enterprises building AI voice agents for call centers
- →Agencies building white-labeled AI agents for clients
- →Conversation designers prototyping and testing dialogue flows
- →Building AI agents and chatbots
- →Creating RAG-based knowledge apps
- →Deploying LLM apps at enterprise scale