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Python boilerplate for quickly building and monetizing AI-powered Telegram bots, with payments, DALL-E images and multi-model support.
Enterprise AI agent platform for building, deploying, and governing no-code agents across company knowledge and workflows.
AI coding platform and IDE that orchestrates multiple agent sessions and lets teams plug in their own AI subscriptions.
Enterprise platform for designing, launching, and scaling AI agents across voice and chat customer experience channels.
Free trial available
No public pricing
No public pricing
Free trial available
- ✦Python boilerplate for AI Telegram bots
- ✦Switch between 5 models including GPT-4o
- ✦Multimodal input (voice notes, images, text)
- ✦Telegram payments and subscription integration
- ✦MongoDB storage and access control
- ✦DALL-E 3 image generation and predefined agents
- ✦No-code visual agent builder
- ✦Company knowledge search across docs and wikis
- ✦Scheduled and recurring agent automations
- ✦Model-agnostic access to major AI models
- ✦Browser extension integration with 30,000+ apps
- ✦Data analysis of spreadsheets and reports
- ✦Enterprise SSO/SCIM/SAML and dedicated deployment
- ✦AI coding IDE with agent orchestration
- ✦Run and manage multiple agent sessions
- ✦Task, artifact and collaboration tools
- ✦Bring-your-own AI subscription or API keys
- ✦Cloud-scale agent execution
- ✦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
- →Ship a monetized AI Telegram bot quickly
- →Build community-specific AI agents
- →Add paid subscriptions to a bot
- →Offer image generation inside Telegram
- →Automating recurring reports and workflow tasks
- →Searching internal company knowledge with AI agents
- →Deploying AI copilots for sales, support, or legal teams
- →Running enterprise AI with strict data governance requirements
- →Shipping code faster with AI agents
- →Coordinating agent work across a team
- →Managing tasks and artifacts in one place
- →Running many parallel agent sessions
- →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