Advanced conversational AILarge context window (200K+ tokens)File upload and analysis (PDF, TXT, etc.)Code writing and explanationCreative and technical writingWeb search capabilities (in certain versions)
Features
Agent Operating Procedures (AOPs) for natural-language workflow definitionOmnichannel support: voice, chat, and email in unified platformVoice AI agents with natural dialog and brand customizationTesting, observability, and experimentation toolsAnalytics suite for conversation insights and customer understandingCross-channel memory for connected interactionsRapid iteration without engineering sprints
Pricing Tiers
Pricing Tiers
Free0/forever
Pro20/month
Max100/month
Team Standard seat25/month
Team Premium seat125/month
EnterpriseCustom/seat
Pricing Tiers—
Integrations
Integrations
SlackNotionVarious developer tools via API
Integrations—
Platforms
Platforms
webiosandroidapi
Platforms
webapi
Pros
Pros
Industry-leading large context window for long documents
Strong focus on safety and reduced harmful outputs
Excellent at complex reasoning and detailed writing tasks
Pros
Multi-channel deployment across voice, chat, and email with unified agent memory
Human-like conversation quality with brand consistency across customer interactions
Agent Operating Procedures enable customizable and optimizable AI agent behavior
Enterprise-focused platform designed for scalable customer service automation
Seamless cross-channel experience reduces customer friction and improves satisfaction
Cons
Cons
Can be overly cautious or refuse certain requests
Less advanced multimodal features (e.g., image generation) vs. some competitors
API access can be more expensive for high-volume use
Cons
Limited information available about pricing and cost transparency for enterprises
Requires technical expertise and integration effort for deployment and optimization
Potential challenges maintaining accuracy and context in complex multi-turn conversations
Competition from established AI platforms with larger ecosystems and customer bases
Dependency on continuous training and tuning for optimal agent performance