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Product growth platform for SaaS teams building in-app onboarding, surveys, and analytics without engineering resources.
Bundles many AI models for chat, writing, image, audio and video into one affordable credit-based app.
Open-source RAG infrastructure with SDKs and an API for developers to build accurate, cited AI chat and search on their own data.
Developer API that gives AI agents persistent memory, retrieval, and connectors, usable both as infrastructure and a personal app.
AI finance agent for investors who want to follow top-trader strategies and auto-trade across connected wallets and brokers.
Free trial available
No public pricing
- ✦No-code builder for tooltips, banners, spotlights, and onboarding flows
- ✦Event autocapture with funnel, trend, and cohort analytics
- ✦NPS, CSAT, and behavior-triggered in-app or email surveys
- ✦Unlimited session replay with rage-click and error detection
- ✦Lia AI agent that surfaces insights and can execute in-app changes
- ✦MCP server for connecting Userpilot data to other AI tools
- ✦AI chat across multiple models
- ✦AI writing and copy tools
- ✦Image generation, upscaling and editing
- ✦Document analysis and chat
- ✦Audio and video generation
- ✦Shared, rollover credit system
- ✦Managed RAG pipeline (extraction, chunking, retrieval)
- ✦Automatic source citations
- ✦Multimodal support (images, tables, graphs)
- ✦Model-agnostic: choose vector DB, embeddings, LLM
- ✦Metadata filtering
- ✦MCP server and AI SDK integration
- ✦22+ file-format ingestion
- ✦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
- ✦Connects wallets, exchanges, and brokers into one portfolio view
- ✦Lets users follow AI agents modeled on top investor strategies
- ✦Supports switching between GPT, Claude, Gemini, and finance-specific models
- ✦Installable 'skills' encode trading strategies and investment frameworks
- ✦Plugins pull in market data, news, and on-chain signals
- ✦Can execute natural-language or automated trades through linked accounts
- →Building guided onboarding flows to improve activation
- →Announcing and measuring adoption of new product features
- →Deflecting support tickets with proactive in-app guidance
- →Spotting at-risk or expansion-ready accounts from usage data
- →Producing marketing and social content
- →Generating and enhancing images
- →Summarizing and querying documents
- →Brainstorming with multiple AI assistants
- →Build a chatbot over private documents
- →Add semantic or deep search to an app
- →Ground answers in a large corpus with citations
- →Ship production RAG without building it in-house
- →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
- →Following a proven trader's strategy with your own capital
- →Building a custom AI trading agent with chosen skills and plugins
- →Monitoring multi-market portfolio exposure in one dashboard
- →Automating trade execution based on live market signals