AI app for marketing · no coding needed
Plain-language data insight and dashboard workspace
Reduce dependence on rented BI tools and analyst queues while keeping data in the client's own environment.
Made for: Marketing and operations teams that need answers from their own databases without writing SQL
What it does for you
The problem
Business teams depend on analysts or rented BI subscriptions to turn stored data into charts, dashboards and answers.
What it gives you
Reviewed dashboards, charts and plain-language answers linked to source queries
What you give it
Connected data sourcesmetric definitionsaccess rulesreporting questions
Build your own version of Basedash, Athenic AI and more
One app with what these 10 AI tools do, yours to keep and change: Basedash, Athenic AI, Supaboard AI, Typper BI, Conduit.app, NBI.AI, Onvo AI, MindsDB Anton, Basedash Self-Hosted, Genie by Databox.
Everything these tools do, in one app
- Natural Language Querying Ask questions in everyday language to get data insights without writing SQL or code.Found in Basedash, Athenic AI, Supaboard AI and 6 more
- Dashboard Creation Create customizable dashboards to track key metrics and visualize data.Found in Basedash, Athenic AI, Supaboard AI and 5 more
- Multi-Source Data Integration Connect to multiple data sources like SQL, NoSQL, APIs, and spreadsheets for unified analysis.Found in Basedash, Athenic AI, Supaboard AI and 6 more
- Real-Time Analytics Analyze live data to get up-to-date insights and performance metrics.Found in Athenic AI, Genie by Databox
- Automated Data Processing Automate data handling and workflow management to improve efficiency.Found in Athenic AI, Conduit.app
- Collaboration Tools Share dashboards, reports, and analyses to support team projects and communication.Found in Athenic AI, Typper BI, NBI.AI and 1 more
- AI-Powered Analysis Use AI to interpret data and generate actionable insights with minimal user input.Found in NBI.AI, MindsDB Anton
- Embedded AI Chat Interact with data through an AI chat interface within dashboards for deeper exploration.Found in Supaboard AI
- Data Privacy and Security Ensure sensitive data is protected with measures like siloing and compliance.Found in Supaboard AI, Basedash Self-Hosted, Onvo AI
- Self-Hosting Options Deploy the platform on your own infrastructure for maximum control and security.Found in Basedash Self-Hosted
- Workflow Automation Automate repetitive tasks and integrate apps with a drag-and-drop builder.Found in Conduit.app
- Version Control Manage versions of dashboards and workflows with features like Git-like control.Found in Onvo AI, Basedash Self-Hosted
- Role-Based Access Control Assign permissions to users to control access to data and dashboards.Found in Onvo AI, MindsDB Anton
- Scheduled Automations Schedule automated tasks and updates for dashboards and reports.Found in Onvo AI
- Activity Logs Monitor workflow performance and track activities with detailed logs.Found in Conduit.app
- Saving Conversations Save queries and results for easy reference and ongoing analysis.Found in Typper BI
- Industry-Specific AI Analysts Leverage AI analysts trained for specific industries to deliver context-aware insights.Found in Supaboard AI
- Open Source Availability Access and modify the source code for customization and transparency.Found in MindsDB Anton
How it works, step by step
- Ask questions in everyday language and return SQL-backed answers
- Generate charts and tables from returned results
- Build customizable dashboards for tracked metrics
- Connect SQL, NoSQL, API and spreadsheet sources
- Refresh dashboards against live data
- Automate recurring data handling and workflow steps
- Share dashboards and analyses with named teammates
- Generate AI-written interpretations of result sets
- Provide an embedded chat panel inside each dashboard
- Apply data siloing, access rules and compliance settings
- Support self-hosted deployment on client infrastructure
- Automate repetitive tasks with a drag-and-drop builder
- Version dashboards and workflows with change history
- Assign role-based permissions per user and dataset
- Schedule automated dashboard and report updates
- Keep activity logs of queries, edits and refreshes
- Save conversations and queries for later reference
- Apply industry-specific analyst context packs
- Allow source-code access for customization
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned reviewed dashboard set with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Plain-language data insight and dashboard workspace with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Plain-language data insight and dashboard workspace with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links5 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare24 KB
- prompt-vps.mdThe same build on your own server (Docker)24 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria11 KB
- demo/index.htmlThe working demo on sample data198 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce dependence on rented BI tools and analyst queues while keeping data in the client's own environment. For marketing and operations teams that need answers from their own databases without writing SQL, convert connected data sources, metric definitions, access rules and reporting questions into reviewed dashboards, charts and plain-language answers linked to their source queries. The benefit is a testable hypothesis, measured through accepted answers per analyst hour and corrections after dashboard approval; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect connected data sources, metric definitions, access rules and reporting questions, then follow this sequence: 1. Ask questions in everyday language and return SQL-backed answers. 2. Generate charts and tables from returned results. 3. Build customizable dashboards for tracked metrics. Resolve uncertain cases with qualified reviewers, approve reviewed dashboards, charts and plain-language answers linked to source queries, and measure accepted answers per analyst hour and corrections after dashboard approval against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One fixed data source set and metric dictionary; final metric definitions and access decisions remain with the data owner. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve data ownership, source attribution, metric accuracy and access permissions. Data owners approve metric definitions and sharing scope. One fixed data source set and metric dictionary; final metric definitions and access decisions remain with the data owner. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One fixed data source set and metric dictionary; final metric definitions and access decisions remain with the data owner. Implement one approved source format, a bounded representative question set and the first two task modules: ask questions in everyday language and return SQL-backed answers; generate charts and tables from returned results. Support the third module with operator review: build customizable dashboards for tracked metrics. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Client-owned databases, spreadsheets, APIs and internal metric dictionaries. Cloud data warehouses, spreadsheet import/export and reporting destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Data source connections, Ask and explore, Dashboard builder, Review and publish. Use a project list for workspaces, a central question box with result table and chart, and a right-hand panel for sources, metric definitions and comments. Let users compare saved queries side by side. Display draft, changes requested and approved states. Provide a shared dashboard link with comments anchored to the relevant chart. Make the task-specific outcome reviewed dashboards, charts and plain-language answers linked to source queries visible beside its evidence, review state and value baseline.
