AI app for customer support · no coding needed
Spreadsheet-backed support assistant and intake console
Reduce manual lookup and re-keying while keeping the spreadsheet as the system of record.
Made for: Support and operations teams that keep their working data in spreadsheets

What it does for you
The problem
Support answers and intake answers live in spreadsheets, so staff re-key questions into chat tools and re-type replies back into sheets.
What it gives you
Reviewed assistant answers and collected intake rows linked to their source cells
What you give it
Permitted spreadsheet rangescolumn definitionsbrand tone notesescalation rules
Build your own version of Botsheets DB, Botsheets and more
One app with what these 3 AI tools do, yours to keep and change: Botsheets DB, Botsheets, Kommunicate with Spreadsheets.
Everything these tools do, in one app
- Chatbot data querying Allows users to ask questions in natural language and get answers from spreadsheet data.Found in Botsheets DB, Kommunicate with Spreadsheets
- Chatbot data collection Uses a chatbot to ask users questions and collect their responses directly into a spreadsheet.Found in Botsheets
- Google Sheets integration Connects with Google Sheets to use spreadsheets as the data source or destination.Found in Botsheets DB, Botsheets
- Multiple spreadsheet support Enables training a chatbot on multiple spreadsheets at once.Found in Botsheets DB, Kommunicate with Spreadsheets
- Real-time synchronization Keeps chatbot responses up to date automatically when spreadsheet data changes.Found in Botsheets DB
- Read and write data Lets the chatbot both read from and write back to spreadsheets during conversations.Found in Botsheets DB
- Flexible query options Provides multiple ways to retrieve data, such as SQL and semantic search.Found in Botsheets DB
- Varied response formats Delivers answers in formats like text, tables, charts, carousels, and markup.Found in Botsheets DB
- Multilingual interaction Supports conversations in multiple languages for diverse audiences.Found in Botsheets
- Data import Allows importing data to tailor chatbot responses.Found in Botsheets
- Secure data handling Provides secure analysis, sharing, and export of data.Found in Botsheets
- Google Workspace output Transforms data into presentations in Google Slides and reports in Google Docs.Found in Botsheets
- Customizable training Lets users customize chatbot training to match brand tone and context.Found in Kommunicate with Spreadsheets
- External platform integration Connects with websites, mobile apps, messaging platforms, and ticketing tools like Zendesk and Freshdesk.Found in Kommunicate with Spreadsheets
- Mobile-friendly deployment Enables chatbot use on Android and iOS devices.Found in Kommunicate with Spreadsheets
How it works, step by step
- Connect Google Sheets as source and destination
- Train one assistant on multiple spreadsheets at once
- Answer natural-language questions from spreadsheet data
- Offer SQL and semantic query options
- Return text, tables, charts, carousels and markup
- Ask users questions and collect responses into a spreadsheet
- Read from and write back to sheets during a conversation
- Keep answers current when sheet data changes
- Import data to tailor responses
- Support conversations in multiple languages
- Customize training to brand tone and context
- Handle data securely with scoped sharing and export
- Transform data into Google Slides decks and Google Docs reports
- Connect to websites, mobile apps, messaging platforms and ticketing tools
- Deploy on Android and iOS
- Capture corrections and named-owner approval before consequential use
- Export a versioned reviewed answer and intake row 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 Spreadsheet-backed support assistant and intake console 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 Spreadsheet-backed support assistant and intake console 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 links3 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare26 KB
- prompt-vps.mdThe same build on your own server (Docker)26 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria13 KB
- demo/index.htmlThe working demo on sample data196 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 manual lookup and re-keying while keeping the spreadsheet as the system of record. For support and operations teams that keep their working data in spreadsheets, convert permitted spreadsheet ranges, column definitions, brand tone notes and escalation rules into reviewed assistant answers and collected intake rows linked to their source cells. The benefit is a testable hypothesis, measured through questions answered without manual lookup and intake rows captured without re-keying; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect permitted spreadsheet ranges, column definitions, brand tone notes and escalation rules, then follow this sequence: 1. Connect Google Sheets as source and destination. 2. Train one assistant on multiple spreadsheets at once. 3. Answer natural-language questions from spreadsheet data. 4. Ask users questions and collect responses into a spreadsheet. Resolve uncertain cases with qualified reviewers, approve reviewed assistant answers and collected intake rows linked to their source cells, and measure questions answered without manual lookup and intake rows captured without re-keying against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate answers and intake questions for the 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 approved spreadsheet schema and one brand tone guide; final policy answers and escalation decisions remain human. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve source attribution, data accuracy, privacy and usage permissions. Named owners approve substantive answers and escalation scope. One approved spreadsheet schema and one brand tone guide; final policy answers and escalation decisions remain human. 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 approved spreadsheet schema and one brand tone guide; final policy answers and escalation decisions remain human. Implement one approved input format, a bounded representative case set and the first two task modules: connect Google Sheets as source and destination; train one assistant on multiple spreadsheets at once. Support the remaining modules with operator review: answer natural-language questions from spreadsheet data; ask users questions and collect responses into a spreadsheet. 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
Google Sheets, Google Slides, Google Docs, websites, mobile apps, messaging platforms, Zendesk and Freshdesk. 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 and column mapping, Assistant builder and test chat, Administrator console and intake queue. Use a source list for connected spreadsheets, a central chat canvas with a right-hand panel for citations, confidence and escalation, and a table view for collected rows and write-back status. Let users compare draft and published assistant versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant answer or row. Make the task-specific outcome reviewed assistant answers and collected intake rows linked to their source cells visible beside its evidence, review state and value baseline.





