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AI customer-support automation with cobrowsing that resolves tickets by extracting answers from help docs and past tickets.
Agentic coding platform (Cosmos) that runs software-dev agents at org scale, using a codebase context engine to cut token cost.
Developer framework and LlamaParse service for parsing documents and building AI agents and RAG workflows over them.
Developer API that gives AI agents persistent memory, retrieval, and connectors, usable both as infrastructure and a personal app.
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No public pricing
No public pricing
- ✦AI ticket automation across channels
- ✦Cobrowsing for guided support
- ✦Answers extracted from help docs and past tickets
- ✦Step-by-step guided resolutions
- ✦Support analytics and content-gap detection
- ✦One-click integrations with existing helpdesks
- ✦Context Engine for codebase understanding
- ✦Agents across the full SDLC
- ✦Model routing / bring-your-own-keys
- ✦Automated code review and test coverage
- ✦CLI, MCP and native tool integrations
- ✦Enterprise security (SOC 2, ISO 42001, SSO)
- ✦LlamaParse document parsing and extraction
- ✦Open-source framework for AI agents and workflows
- ✦Document indexing for retrieval/RAG
- ✦Prebuilt solutions by industry and use case
- ✦Free starter credits for LlamaParse
- ✦Lifelike voice AI agents
- ✦24/7 availability
- ✦Customer-led conversational platform
- ✦Integration with enterprise systems
- ✦Persistent, structured memory built as a knowledge graph
- ✦Sub-300ms hybrid retrieval (RAG) with reranking
- ✦Native filesystem mount for agent memory access
- ✦Connectors to Slack, Notion, Drive, Gmail, GitHub, S3
- ✦Automatic extraction from PDFs, images, and audio
- ✦User profile and behavior tracking across sessions
- →Automatically resolve common support tickets
- →Deflect inquiries with self-serve answers
- →Guide customers through resolutions
- →Cobrowse to assist users in real time
- →Spot content gaps and trends
- →Automating PR code review
- →Raising test coverage
- →Incident investigation and remediation
- →Large-scale migrations and onboarding
- →Parse complex documents for AI apps
- →Build RAG and agent workflows
- →Automate invoice and claims processing
- →Search across technical documents
- →Answering customer service calls
- →Providing information and support
- →Resolving customer issues
- →Automating call center operations
- →Developers adding long-term memory to AI agents
- →Teams building agents that need to sync with existing tools
- →Individuals wanting one memory layer shared across multiple AI assistants