Keep the evidence, the analysis, and the readout together. A built-in AI agent, real spreadsheets, and presentations in your institution's template, so the coded data, the report that interprets it, and the deck you present never drift apart.
Research output is only as good as its trail. When the data sits in one tool, the analysis in another, and the readout in a third, the link between a conclusion and its evidence gets lost in the move. Skybits is an AI collaborative document editor where the output is already a reviewable report, a spreadsheet with working formulas, or a deck in your own template. Use the built-in Skybits agent with no setup, or connect ChatGPT, Claude, Cursor, Gemini, or Perplexity over MCP when a specific model suits the task. Both write to the same documents, under the same review gate.
1. Draft the Research Report with a Built-In AI Agent, No Setup
Why Every Co-Author Has to Configure a Tool First
You have transcripts to work through today. The AI tool wants an API key or an MCP client configured first, and every co-author needs the same setup before they can contribute.
How the Built-In Skybits Agent Works Through Your Transcripts
Open Skybits and ask. The built-in Skybits agent creates the report with the structure you specify and works through your material section by section. Nothing to install. When a specific model suits a specific task, connect ChatGPT, Claude, Cursor, Gemini, or Perplexity over MCP. Both work on the same documents, so you can use one model for synthesis and another for sourcing.
Example Prompt: Build a Research Report from Interviews
"Create a research report from these twelve interview transcripts. Include Method, Key Themes with supporting quotes, Contradicting Evidence, Limitations, and Recommended Next Steps. Attribute every quote to its participant ID."
What You Get: A Structured Report, No Per-Author Setup
- A structured report in minutes, with no configuration first
- No per-author setup before co-authors can contribute
- Best-of-breed models over MCP whenever a task calls for one
2. Keep Coded Data and Survey Results Next to the Findings
Why Tracing a Number Back to Its Evidence Takes Three Tools
Survey results sit in a spreadsheet in one tool, coded interview data in another, and the report in a third. When a reviewer asks how you reached a number, you are reconstructing the path across three tools.
How Skybits Spreadsheets Hold the Coding Frame
Skybits spreadsheets are full documents: multiple tabs, real formulas, conditional formatting, named ranges. Ask the agent to build the coding frame, the survey summary, or the comparison matrix, and keep it beside the report that cites it, under the same permissions. Export to XLSX, ODS, or CSV for statistical tools or for a data appendix.
Example Prompt: Build a Thematic Coding Workbook
"Build a thematic coding workbook: one tab per theme, one row per coded excerpt with participant ID and source, and a summary tab counting excerpts per theme with percentage of participants."
What You Get: Evidence and Findings Under One Permission Set
- Data and findings in one workspace, under one permission set
- Working formulas and conditional formatting, not a static table
- Clean export to XLSX, ODS, or CSV for analysis tools and appendices
3. Turn Findings into a Readout Deck in Your Own Template
Why the Readout Is Hours Away After the Analysis Is Done
The analysis is finished and the readout is still hours away, because the findings have to be rebuilt slide by slide in the institution's or the client's template.
How to Get On-Brand AI Slides from Your Institution's Template
Upload your organisation's deck once and set it as a template. From then on, ask for a presentation and it is built in that template. No file to upload? Ask the agent, or your own model over MCP, to build the template from your website's brand styles, and it is constructed from scratch. Decks are Canvas documents: share by link with stakeholders, or export to PDF for the record.
Example Prompt: Generate a Findings Readout
"Create a findings readout from our template: method, four key themes with one supporting quote each, contradicting evidence, and recommendations. Use the research report and the coding workbook as sources."
What You Get: Readouts Built from the Report and the Data
- One template upload, every readout on brand after that
- A brand template built from your website when you have no file to start from
- Decks generated from the report and data you already produced
4. Review Every AI Change Before It Enters a Finding
Why AI Is Useful for Synthesis and Dangerous for Evidence
AI is useful for synthesis and dangerous for evidence. A confident sentence that overstates what the data supports is the one thing that must never reach a published finding, and chat tools give you no review step.
How Suggest Mode Gives You a Defensible Audit Trail
Suggest Mode holds every AI edit as a pending proposal. Whether it came from the built-in agent or from your own model over MCP, you see the tracked diff, accept what the evidence supports, and reject the rest. Version history records who proposed what, which gives you a defensible trail for peer review.
Example Scenario: Rejecting an Overstated Claim
You ask for a sharper synthesis of theme three. Five edits come back. You accept four, and reject one that generalises from two participants to the whole sample. Nothing entered the report without a check against the data.
What You Get: An Attribution Trail That Survives Peer Review
- A human approval gate on every change to a finding
- Accept or reject per suggestion, not all or nothing
- An attribution trail that stands up to peer review
5. Keep Reviewer Challenges Anchored to the Claim
Why the Reasoning Behind a Conclusion Ends Up in Three Places
A co-author questions a conclusion by email. A reviewer marks up a PDF. A third comment arrives in chat. The reasoning behind the final wording ends up in three places and none of them is the document.
How Role-Based Access Works for Co-Authors and Reviewers
Share with role-based access: co-authors as editors, reviewers as commenters, sponsors as viewers. Comments anchor to the exact sentence they question, so the challenge and the claim stay together. Ask the agent to revise from a thread, review the suggestion, resolve the thread. The discussion behind every conclusion stays attached to it.
Example Workflow: Qualifying a Claim After Review
- A reviewer comments on a conclusion: "Two participants said this, the other ten did not raise it."
- You reply in-thread, then ask the agent to qualify the claim to match the count.
- The suggestion appears, you accept it, and the thread is resolved as a record of the challenge.
What You Get: A Record of How Each Conclusion Was Settled
- Challenges anchored to the exact claim they concern
- Role-based access for co-authors, reviewers, and sponsors
- A record of how each conclusion was questioned and settled
Skybits for Researchers and Analysts at a Glance
| Capability | What it replaces | Impact |
|---|---|---|
| Built-in agent | Per-author AI setup before work starts | Every co-author productive immediately |
| Spreadsheets | A separate tool for coded data and survey results | Evidence and findings under one permission set |
| Canvas decks from your template | Rebuilding findings slide by slide | Readout generated from the report and data |
| Suggest Mode | Manually checking AI claims against the data | Nothing enters a finding unreviewed |
| Inline comments | Email, PDF markup, and chat review threads | Challenges anchored to the claim itself |
| MCP with your own model | Juggling AI tabs and stitching output | Any model, one document |
Skybits vs Google Docs, Notion AI, and Claude Artifacts
| Looking for… | The alternative | Why researchers choose Skybits |
|---|---|---|
| Google Docs alternative for AI | Google Docs plus an AI sidebar | Google Docs bolts AI on. Skybits has a built-in agent, MCP access for your own model, and a suggest-and-reject gate before anything enters a finding. |
| Notion AI alternative for documents | Notion AI | Notion locks you to one model. Skybits gives you a built-in agent and any MCP model, plus spreadsheets with real formulas for coded data. |
| AI presentation maker | Generic AI deck tools | Generic tools give you their template. Skybits builds readouts in your template, from an uploaded file or from your website's brand styles. |
| Claude Artifacts alternative | Claude Artifacts | Artifacts live inside a chat session. Skybits turns the output into a persistent, citable document with full version history. |
Frequently Asked Questions
Do co-authors need to configure anything before they can contribute?
No. The built-in Skybits agent works from an empty workspace, so every co-author is productive immediately without an API key, an MCP client, or a local install.
Can I use Perplexity for sourcing and Claude for synthesis?
Yes. Connect ChatGPT, Claude, Cursor, Gemini, or Perplexity over MCP. Each writes to the same documents under the same review gate, so you can use one model for sourcing and another for synthesis without moving the work.
How does Skybits stop AI from overstating what the data supports?
Suggest Mode holds every AI edit as a pending proposal rather than an edit. You see the tracked diff, accept what the evidence supports, and reject the rest. Version history records who proposed what.
Can I keep coded interview data in the same place as the report?
Yes. Skybits spreadsheets are full documents with multiple tabs, working formulas, conditional formatting, and named ranges, so a coding workbook sits beside the report that cites it under the same permissions.
Can I export data for statistical tools or a data appendix?
Spreadsheets export to XLSX, ODS, or CSV. Readout decks are Canvas documents, shareable by link and exportable to PDF for the record.
Can Skybits build a readout in my institution's template?
Yes. Upload the deck once and set it as a template, and every readout after that is built in it. With no file to upload, the agent can construct the template from your website's brand styles.
Start with One Report
Take the transcripts sitting on your desk and ask for the report. Nothing to configure, and the coding workbook and the readout deck can follow into the same workspace. The point is not speed for its own sake. It is that the conclusion, the evidence behind it, and the slide you present stay attached to each other.
