Basedash

What it is

Basedash is an AI-native business intelligence platform that lets you create charts and dashboards using natural language. Instead of manually writing SQL queries or clicking through complex chart builders, you describe what you want to see and the AI generates the dashboard. You can also chat with your data to ask follow-up questions and drill deeper, and the docs say the AI picks the chart type and formatting for you. The platform connects to Snowflake, BigQuery, PostgreSQL, Databricks and other warehouses or operational databases, and its solutions page offers pages for product, sales, marketing and ecommerce teams, plus PostgreSQL setups such as RDS, Supabase and Neon.

What you build and how

Natural language dashboards and insights. Describe what you want to see ("Show me monthly revenue growth" or "Compare sales by region") and Basedash generates the dashboard, complete with the right visualizations and charts. You chat with your data by asking follow-up questions, drilling deeper into insights without manually building new queries. Dashboards can be shared across your organization. The solutions page frames this as self-service analytics for operational, product, revenue and customer metrics "without SQL", so PMs, operators and revenue teams can ask questions without waiting on an analyst.

Data connections. Basedash connects to over 750 data sources, spanning databases, cloud apps, data warehouses, files and APIs. Both plans also include the Basedash Warehouse, listed on the pricing page alongside the 750+ sources. The ecommerce solution page talks about connecting Shopify, ads, payments and fulfillment data to report blended ROAS, LTV by channel and profit per order. You connect your data sources and start creating dashboards; the features page says getting started takes under 30 minutes, and the team offers to help migrate data and dashboards from another tool.

AI data analyst and automations. The platform includes an AI data analyst, described as trusted answers from your data. You can also build AI-powered data workflows and automations directly in the platform, and the site links to automation templates and dashboard templates as starting points. The features page also lists Insights, described as AI-generated daily data briefings, and Skills. An MCP server lets you connect any AI client to your data, and a Slack app brings the analyst into Slack.

Embedded analytics for SaaS. Use embedded analytics when the BI experience needs to live inside your own product. Basedash supports customer-facing dashboards, white-label embedding, row-level security, SSO and governed analytics so each customer sees the right data without your team building a dashboard system from scratch. The solutions page adds secure customer portals and embedded AI analytics to that list.

Models and data modeling. The features page lists Models as AI-first data modeling, and the docs navigation also covers a SQL editor, AI context, data source access control and row level security. One sample chat on the home page reads a governed metric definition, an MRR figure that excludes trials, before it builds a revenue and signups dashboard. That is the point of the modeling layer: definitions are set once so that every generated chart uses the same numbers.

Team collaboration. The docs describe inviting your team and sharing dashboards and insights across your organization, and the docs navigation lists domains and SSO and SCIM provisioning, which the features page describes as syncing users and groups from your identity provider. The pricing page lists audit logs and custom AI models among the Enterprise plan features.

Security and deployment. Self-hosting is available for teams that require tighter network control, internal infrastructure alignment or stricter compliance requirements. Organizations can also deploy in VPC-based environments as needed. The docs navigation lists self-hosting overview, deploy and configure pages.

Plans, pricing and security claims

Pricing is the most specific part of the site. The pricing page describes "Flat-rate plans instead of per-seat licensing" and offers a 14-day free trial with no credit card required and, per the FAQ, full feature access, so a team can connect its data and generate dashboards before committing.

There are 2 plans. Startup is "$1,000 /month + AI usage" and includes up to 25 users, 750+ data sources, $1,000 a month in AI credits, Slack support, the Basedash Warehouse, the MCP server, the Slack app, automations and insights. The FAQ says the plan lets teams "invite operators, analysts, executives, and other decision makers without pricing every viewer as a separate license," and gives a 15-person sales, operations or startup team a budget of $1,000 a month plus AI usage. Enterprise is custom priced and adds custom seats, dedicated support, self-hosting, embedding, SSO, SCIM, audit logs and custom AI models, and the FAQ says Enterprise plans support custom user counts, deployment models, security controls and procurement requirements.

AI usage works on credits. "Every plan comes with free monthly AI usage credits," the FAQ says; most AI actions, like asking a question in chat or generating a dashboard, count towards usage, and going over the free monthly limit means usage fees on your next bill, which you can track in the Billing section of the app. The pricing page also mentions non-profit discounts, available by talking to the company.

On security, the pricing FAQ says controls include "SOC 2 Type II compliance, encryption in transit and at rest, and strict data access boundaries," and that customer data is never used to train models. It lists role-based access controls, single sign-on with SAML and OIDC, SCIM user provisioning, native audit logs and trusted metric definitions, and says Basedash supports enterprise procurement workflows such as security reviews and legal review cycles. The footer links a DPA, a security page and a compliance page.

On connectivity, the features page says "Connect 750+ data sources," and the solutions page names Snowflake, BigQuery, PostgreSQL and Databricks as examples, with a PostgreSQL page noting JSONB support and compatibility with RDS, Supabase and Neon.

Who it suits and who it does not

Basedash fits a startup or mid-size team that keeps its numbers in Postgres or a warehouse and wants business users to ask questions and get charts without opening a ticket with a data team. Product, sales, marketing and ecommerce leads are the audiences its solutions page speaks to, and the flat 25-user tier means a whole sales or operations team can get access without seat math. A SaaS company that wants customer-facing dashboards inside its own product, with white-label embedding, SSO and row-level security, is the other clear match, and an IT team that needs self-hosting, a VPC deployment, audit logs or a SOC 2 Type II report has an answer on the pricing page, on the Enterprise plan.

The cost model is the main caveat. The entry point is $1,000 a month plus AI usage, so a solo founder with one small dashboard will find it expensive, and heavy chat or dashboard generation past the included credits adds usage fees. Embedding, self-hosting and SSO sit on the custom Enterprise plan rather than Startup. Because the product is AI-first, someone should still check generated charts against known numbers before sharing them widely.