Livedocs
LiveDocs is an AI native data workspace that combines a notebook style IDE, a general data agent, and lightweight app building in a single browser based tool. Users upload files or connect databases, then ask questions in natural language, SQL, or Python to get answers, charts, and shareable interactive reports without wrestling with infrastructure.
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- Already use it? Add Livedocs to Stack Autopsy — check cost, overlap and safe cancellations.
- Thinking about buying it? Ask AI Advisor — compare fit, alternatives and trade-offs.
- Want to leave it? Find a replacement — see feature losses and migration risks.
Pricing
- Free: $0 per month; includes unlimited docs and apps, 8 GB RAM with 2 vCPU, $5 monthly AI credits, Livedocs Anywhere (local use), and email and Discord support.
- Pro: $30 per workspace per month plus $20.00 per additional member; includes 32 GB RAM with 4 vCPU, unlimited members, real-time collaboration, scheduled runs, terminal access, data integrations (Snowflake, Databricks, BigQuery), and multi-platform notifications.
- Custom: Custom pricing; includes on-premise deployment, SSO and custom authentication, custom machine profiles, dedicated support and onboarding, and data project consulting. Book a demo with the sales team to see all pricing options.
Features
- AI data agent for “ask then analyze”: An integrated agent sits on top of CSVs, spreadsheets, and databases, using tools like DuckDB, web search, and a terminal to answer questions, transform data, and explain results in plain language.
- SQL, Python, and AI in one IDE: LiveDocs lets users write SQL and Python side by side, call AI to fix or generate code, and pass data between cells for exploratory analysis, modeling, and visualization in a single notebook style document.
- High performance data engine: Under the hood it favors fast technologies like Polars DataFrames and DuckDB queries, giving noticeably quick feedback on large datasets compared with many browser based BI tools.
- Interactive apps and sharing: Any notebook can be turned into an interactive app where stakeholders see inputs, filters, and charts while the code stays hidden, making it easier to ship live dashboards instead of static screenshots.
Use cases
- Data Analysts: Turning warehouse data into narratives with charts, tables, and explanatory text that can be shared as interactive apps.
- Data Scientists: Prototyping models, running experiments in Python, and documenting findings for mixed technical and non technical audiences.
- Product, Growth, and Marketing Teams: Running churn analyses, A/B test readouts, demand forecasts, and cohort deep dives without waiting on separate BI teams.
- Founders & Executives: Building quick KPI workspaces and investor friendly views that stay connected to live data instead of static decks.
- Uncommon Use Cases: Used by small analytics agencies to deliver client facing interactive reports instead of PDF exports; adopted by technical support or operations teams who need quick, ad hoc data tools without committing to a heavy BI deployment.