Basedash

Basedash

AI-native BI: ask in plain English, get governed SQL, charts and dashboards from 750+ sources. Flat rate from $1,000/mo.

🔗 Visit Basedash
📁 Data & Analytics🗣️ English

Description

Basedash lets people ask questions about their company's data in plain English — 'how many sign-ups last month?' — and get charts and dashboards back, without writing database queries or waiting for an analyst. Built-in guardrails make sure everyone gets the same, verified definitions of the numbers. Basedash is an AI-native business intelligence platform that lets teams query their data in natural language: prompts are translated into SQL against connected databases and warehouses, returning charts, dashboards and reports without hand-written queries. What separates it from generic chat-with-your-data tools is the governance layer — a semantic catalog of approved metric definitions and verified sources that constrains the AI, so two people asking the same question get the same, auditable answer. It connects to 750+ data sources, supports embedding and workflow automations, exposes an MCP server for agent integrations, and generates automated insights from connected data. Security posture is enterprise-grade: SOC 2 Type II, SSO, role-based access control, row-level security and query audit logs, with an explicit commitment not to train models on customer data, and both cloud and self-hosted deployment. Pricing is flat-rate rather than per-seat: the Startup plan at $1,000/month includes up to 25 users and monthly AI credits, with enterprise plans custom-priced. A 14-day full-feature trial requires no credit card. Basedash reports 200+ companies as customers.

💬 Our review

The short version: a credible 'ask your data anything' tool for mid-size companies — but at $1,000 a month, small teams should start with free alternatives first.

Basedash gets the hard part of AI BI right conceptually: raw text-to-SQL is a demo, not a product, because nothing stops the model from inventing a revenue definition per question. Anchoring generation to a governed semantic layer of verified metrics is the correct architecture, and flat-rate pricing including 25 users counters the per-seat creep that makes classic BI expensive precisely when adoption succeeds. SOC 2, row-level security, audit logs and a no-training commitment cover the enterprise checklist, and self-hosting is available. The honest counterweights: $1,000/month is a real floor — a five-person startup gets far more value per dollar from Metabase (open source, free) or Lightdash until non-technical query volume actually justifies it; it's closed source; the AI-credit metering adds a variable on top of the flat rate that's hard to predict before real usage; and 200+ customers means the semantic layer tooling is younger than dbt-based alternatives it conceptually competes with. Best fit: 20-200 person companies with a data warehouse, no analysts to spare, and a queue of business questions. Below that, start open source and revisit.

💰 Pricing

PaidFlat-rate model: Startup $1,000/month including up to 25 users and monthly AI credits; Enterprise custom; 14-day free trial without credit card
Startup 1000Enterprise

📊 Global score

58Average
🌐Availability15/100Faible

1 language · 0 platform

📄Profile100/100Excellent

Profile completeness

🤖 AI-enriched data

💰 Pricing model💳 Paid· $1,000/mo flat incl. up to 25 users + AI credits; enterprise custom; 14-day trial
👥 Target audienceMid-size companies without analysts | Ops & business teams
🗣️ Languagesen
🌍 Target countriesWorldwide
👍

Pros

Governed semantic layer constrains the AI

Flat rate, no per-seat creep

750+ connectors

👎

Cons

$1,000/mo entry price

Closed source

❓ Frequently asked questions

How is this different from asking ChatGPT to write SQL?
Basedash constrains generation with a governed semantic layer — approved metric definitions and verified sources — so answers are consistent and auditable across users, with RLS and query logs enforcing who sees what.
Who is the $1,000/month Startup plan for?
Teams of roughly 10-25 people with a real data warehouse and recurring business questions but no dedicated analyst. Smaller teams usually get better value from Metabase or Lightdash first.
Does Basedash train AI models on my data?
No — the company explicitly commits to not training models on customer data, and offers SOC 2 Type II compliance, SSO, row-level security and audit logs.
Can it run on our own infrastructure?
Yes, both cloud and self-hosted deployments are offered; self-hosting details are provided during enterprise conversations.
Is it worth the money compared to alternatives?
At $1,000/month flat for up to 25 users, Basedash beats per-seat BI once 15+ people actually use it — but Metabase's open-source core is free forever and Lightdash is open source over dbt. The honest math: pay Basedash when AI answering genuinely replaces analyst hours; otherwise free BI plus occasional SQL help wins.
Which BI tool should you pick for your case?
20-200 person company with a warehouse and no analysts: Basedash. Small team or zero budget: Metabase. dbt-centric data team wanting governed metrics: Lightdash. SQL-fluent team wanting notebooks and apps: Hex.