Give every team self-serve access to data. Ask questions in plain English, get AI-generated dashboards, and share governed metrics — no SQL required.
14-day trial, no credit card required.
Basedash is an AI self-service analytics platform for operational, product, revenue, and customer metrics. Non-technical teams ask questions in plain English, get AI-generated dashboards, and use governed definitions without SQL, analyst tickets, or spreadsheet exports.
What changes when your team can ask data questions directly.
Ticket to the data team, wait 3 days
Ask a question, get the answer in seconds
Spreadsheets with stale exports
Live dashboards connected to your warehouse
Conflicting numbers across teams
Governed metric definitions everyone shares
SQL required for every question
Plain English queries with AI-generated SQL
From marketing to finance, every team gets self-serve access to the data they need.
Marketing
Marketing teams track campaign ROI, attribution, and funnel conversion without waiting for analyst support.
"What was our cost per lead by channel last month?"
Sales
Sales leaders monitor pipeline health, rep performance, and forecast accuracy in real time.
"Which deals are at risk of slipping this quarter?"
Product
Product managers measure feature adoption, retention cohorts, and product analytics alongside revenue and support data.
"What is the adoption rate for the new onboarding flow?"
Operations
Operations teams run operational analytics for SLAs, capacity, process efficiency, and real-time health metrics.
"Show me our support ticket resolution time trend"
Finance
Finance teams monitor MRR, churn, expansion revenue, and unit economics from a single source of truth.
"What is our net revenue retention by cohort?"
Executives
Leadership gets AI-generated briefings on key metrics without scheduling a meeting or opening a spreadsheet.
"Give me a weekly company health summary"
Everything non-technical teams need to explore data independently.
Natural language queries
Ask questions in plain English. The AI generates SQL, runs it against your warehouse, and returns charts and summaries.
AI-generated dashboards
Describe the dashboard you need and Basedash creates it. No drag-and-drop builder, no SQL, no configuration.
Governed metrics
Define business metrics once — MRR, churn rate, active users — and the AI uses those definitions consistently across every query.
Automated insights
Basedash proactively surfaces trends, anomalies, and opportunities in your data. Get daily briefings without asking.
Broad data connectivity
Connect 750+ data sources including warehouses, databases, and SaaS tools. Ask questions that span your entire data stack.
Role-based access
Control who sees what. Basedash supports team-level permissions and inherits your warehouse's access controls.
Get instant answers, uncover important trends, and make confident decisions faster.
Connect your own warehouse, or use Basedash Warehouse to visualize all your data in one place.
See all 750+ integrationsBasedash vs traditional self-service BI
How AI-native self-service compares to legacy BI tools.
| Capability | Basedash | Traditional BI |
|---|---|---|
| Natural language queries | Yes — full conversational | Limited or none |
| AI-generated dashboards | Yes | Manual setup |
| Time to first insight | Seconds | Days (requires analyst) |
| Business context awareness | Custom metric definitions | Schema-only |
| Non-technical user access | Full self-serve | Filtered views or SQL |
| Data source breadth | 750+ sources | Warehouse-only |
| Proactive insights | AI-generated daily | Manual scheduling |
| Self-hosting | Available | Rarely |
Self-service analytics FAQ
What is self-service analytics?
Self-service analytics gives business teams a safe way to explore data, build reports, and answer questions without waiting for an analyst or writing SQL. In Basedash, users ask in plain English while the data team keeps control over data models, permissions, and metric definitions, so faster answers do not come at the cost of governance.
How is AI self-service analytics different from traditional BI?
Traditional BI usually expects users to navigate dashboards, filters, and report builders that someone else configured. AI self-service analytics starts with the business question instead: Basedash turns plain-English requests into SQL, charts, summaries, and dashboards connected to live data. That makes ad hoc analysis easier for operators, product managers, marketers, and executives who know the question but do not know the database schema.
Can non-technical users really use Basedash without training?
Yes. Basedash is designed around natural language interaction, so users type questions the way they would ask a teammate. The AI returns charts, tables, explanations, and follow-up options without requiring a query language or dashboard-builder training. Teams can still save repeatable dashboards once a question becomes part of their regular operating rhythm.
What is operational analytics?
Operational analytics is the practice of tracking live business processes such as support SLAs, sales pipeline movement, onboarding completion, incident volume, fulfillment delays, and capacity constraints. Basedash helps operations teams ask questions against current warehouse and SaaS data, turn recurring checks into dashboards, and surface changes before they become weekly reporting surprises.
Can Basedash support product analytics and business metrics in one place?
Yes. Basedash connects to existing databases, warehouses, and SaaS tools, so product events can be analyzed alongside revenue, customer, support, and operational data. Product teams can ask about activation, retention, funnels, or feature adoption, then combine those answers with account value, customer health, or pipeline context that dedicated event-only tools often keep separate.
How does Basedash prevent conflicting metrics across teams?
Basedash supports governed metric definitions, so the company can define what terms like MRR, active user, churn rate, resolution time, or feature adoption mean once. The AI uses those definitions when answering questions and creating dashboards, which reduces the chance that each team builds its own spreadsheet version of the same metric.
Does self-service mean less control for the data team?
No. Data teams still define the semantic layer, manage source connections, set access permissions, and review how AI-generated queries use company data. Self-service changes who can ask questions and how quickly answers are delivered; it does not remove the governance, security, or modeling work that keeps analytics trustworthy.
What data sources does Basedash support?
Basedash connects to 750+ data sources including Snowflake, BigQuery, PostgreSQL, Salesforce, HubSpot, Stripe, and more. Teams can ask questions that combine product, customer, finance, marketing, and operational data across sources, then save the result as a dashboard or recurring report for ongoing visibility.