Fabi.ai
AI-native data analytics platform with agentic notebooks
Last reviewed 2026-06-19
Fabi.ai is an AI-native data analytics platform built around Smartbooks: collaborative, AI-native notebooks that mix SQL, Python, and no-code so data teams can turn questions into visualizations, dashboards, smart reports, and scheduled workflows. It also ships an Analyst Agent for exploratory data analysis and an MCP server that lets its AI analyst run inside other LLM and chat interfaces. Autonomy is bounded by a human-driven notebook workflow: the agent assists, and analysts review and edit the generated SQL, Python, notebooks, and dashboards before relying on them. Fabi.ai is a commercial SaaS with a free trial and per-seat plans, built by an early-stage team.
What it can do
Explore data with an Analyst Agent
SupervisedAn AI agent runs exploratory data analysis and surfaces insights, which the analyst reviews.
sourceBuild analyses in Smartbooks
CopilotAI-native notebooks let teams mix SQL, Python, and no-code in one collaborative workspace.
sourceGenerate dashboards and smart reports
CopilotTurns a query or question into a dashboard or report quickly for sharing.
sourceAutomate workflows and serve via MCP
SupervisedSchedules runs to deliver insights and exposes an MCP server to embed the AI analyst in external LLM and chat tools.
source
Strengths
- +Broad native connectors across major warehouses and SaaS apps
- +Flexible workflow: SQL, Python, and no-code in one AI notebook instead of one fixed paradigm
- +Ships an MCP server, making the analyst embeddable in other LLM and chat tools
Limitations
- −Small early-stage team, so roadmap depth, support, and longevity carry more risk than incumbents
- −Underlying model(s) are not disclosed and there are no published accuracy benchmarks
- −Per-seat pricing and AI-request limits on lower tiers can add up for larger teams
Overview
Fabi.ai is an AI-native data analytics platform that calls itself the AI analyst for all your data. Its centerpiece is the Smartbook: an AI-native notebook that mixes SQL, Python, and no-code so data teams (and adjacent PM, growth, and finance teams) can move from question to insight in one place.
What it does
An Analyst Agent runs exploratory data analysis and surfaces insights; Smartbooks let people build analyses by combining SQL, Python, and no-code; and a few clicks turn a query into a dashboard or smart report. Scheduled workflows deliver insights on a cadence, and an MCP server lets the AI analyst run inside other LLM and chat tools. The agent assists within a human-driven workflow: analysts review and edit the generated code and outputs.
Integrations & setup
Connects to warehouses and databases (Snowflake, BigQuery, Redshift, PostgreSQL, Databricks, MotherDuck) and SaaS apps (Stripe, HubSpot, Salesforce, Airtable, Google Sheets, PostHog, Google Ads and Analytics, Supabase). The MCP server adds interoperability with external AI clients.
Pricing
Per-seat subscription with tiered plans and a free trial. Entry pricing is reported around $39/month per seat, with higher team tiers; confirm current numbers on the pricing page.
Best for / not for
Best for data teams and data-literate operators who want a flexible AI notebook with broad connectors. Less suited to large enterprises needing a mature, heavily supported BI stack, given the company's early stage.
Alternatives
Hex is the closest data-notebook peer with AI; Julius AI targets conversational analysis; ThoughtSpot offers enterprise natural-language BI.
What people are saying
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FAQ
What is a Smartbook?+
Smartbooks are Fabi.ai's AI-native notebooks that let data teams combine SQL, Python, and no-code in one collaborative workspace, positioned as a next-generation alternative to Jupyter or Colab with an AI analyst built in.
How autonomous is Fabi.ai?+
Its Analyst Agent can run exploratory analysis and generate code and dashboards on its own, but it operates inside a human-driven notebook where analysts review and edit the output, so in practice it is a supervised agent.
Sources
- Fabi.ai (official site) · accessed 2026-06-19
- Fabi.ai pricing · accessed 2026-06-19
- Fabi.ai company profile (Tracxn) · accessed 2026-06-19
Last reviewed 2026-06-19