Last week one of our web pods restarted 11 times in 24 hours, and another restarted 9 times. The app worked, users were happy, and latency was fine. Our application logs had nothing to say about it, just gaps where a process used to be.
We spent a couple of days chasing the wrong thing. Then we found a Kubernetes default we d never thought to override, and the crash loop stopped.
The Basedash semantic layer lets teams create reusable SQL metrics and models that AI can reference across chat, charts, dashboards, insights, and automations.
Basedash Embedding puts the full power of Basedash inside your own product. Drop a dashboard in with one iframe, or embed the whole app so your customers can chat with the AI agent, build their own dashboards, and get automatic insights — without ever leaving you. Row-level security scopes every customer to their own data, and customization controls decide exactly which features they see. Setup is one iframe and a JWT. Analytics, inside your product. Scoped to every customer.
Skills are reusable bundles of instructions that every Basedash AI surface can read on demand.
Define your metrics once and any AI agent in your workspace will pick up the skill when it's relevant. No more pasting the same caveats into every prompt.
Each skill is a short, plain-language playbook for one concept. Admins manage them; everyone else's AI gets the benefit. Add them as you go — the more you teach Basedash, the more it acts like an analyst who already knows your business.
We ve been growing really fast (30%+ MoM ARR) at @Basedash since launching last year. Most of that growth has been the result of hard work, but we ve also had a secret weapon: an AI agent that acts as both a data analyst and a PM, working 24/7 to optimize our product s activation and conversion rates.
For decades, companies have been making product decisions based on intuition and manual data analysis. We wanted to see what would happen if AI could take the wheel completely.
Basedash already reads from your databases, warehouses, and SaaS tools. Now it can act on them too. Connect any MCP server — Linear, HubSpot, Slack, Resend, Notion, GitHub — and the Basedash agent gets new tools it can use right inside chat. Ask it to email your latest signups, file a Linear bug from a support ticket, or update a HubSpot lead based on what a user did in your product. Pair with Automations to run the whole flow on a schedule. Connect any app. Take action anywhere.
Basedash is now an MCP server. Connect Claude, Cursor, ChatGPT, or any MCP-compatible client and your AI agent can ask Basedash anything about your data — across every database, warehouse, and SaaS tool you've already connected to your workspace. It can pull live numbers, compare cohorts, generate charts, and dig into trends, all governed by the same access controls your team already uses. Your data analyst, inside every tool you ship in.
The Dashboard Agent builds entire dashboards from a single prompt. Describe what you want to see — "Everything about new user signups" or "MRR and churn this quarter" — and the agent picks the charts, writes the SQL, and lays them out for you. You get KPIs, a hero chart, and the breakdowns that actually answer your question, all connected to live data. No SQL. No composing dashboards chart by chart.
Describe a dashboard. Get a dashboard.
Basedash is the AI-native Business Intelligence platform. Create dashboards and instantly understand your customers using natural language. Connect 500+ data sources, ask a question, and let Basedash visualize the answer.
Basedash Automations puts your AI data analyst on a schedule. Kick off analyses on a recurring cadence, when your data changes, or on demand — and deliver the results to Slack and email as an AI-written report with an executive summary, key metrics, and charts.
Start from 15+ templates for growth, engineering, sales, finance, customer success, and ops — or describe your own analysis in plain English. No SQL. No dashboards to babysit. Your data works for you while you sleep.
