Every team eventually hits the same wall: the data lives in a spreadsheet, but the person who needs the answer doesn't know how to write the formula, join, or query that gets them there. For years the fix was "ask the one person on the team who's good at Excel." AI has quietly closed that gap — not by replacing spreadsheets, but by putting a translator in front of them that turns plain English into the right formula, model, or database structure.
That's really the throughline connecting the five tools below: Airtable, Rows, Formula Bot, Obviously AI, and Hex. They're not interchangeable — one is a database dressed as a spreadsheet, another is a spreadsheet with a chatbot bolted on, and two of them skip the grid entirely — but each solves a specific flavor of "I have data and I don't know what to do with it next."
In this article
- Airtable: when a spreadsheet needs to behave like a database
- Rows: a spreadsheet that can call the internet
- Formula Bot: the fastest fix for "what formula do I even need"
- Obviously AI: predictions without writing a model
- Hex: a notebook for people who don't want to write in a notebook
- Quick Comparison
- Frequently Asked Questions
- Do I need to know SQL or Python to use any of these?
- Can I just use ChatGPT for this instead of a dedicated tool?
- Which tool should a small business with no dedicated analyst pick?
- Is Formula Bot worth paying for if I only use spreadsheets occasionally?
- Final Verdict
Airtable: when a spreadsheet needs to behave like a database
Airtable looks like a spreadsheet until you try to do something a spreadsheet can't: link records across tables, attach files directly to a row, or build a form that feeds structured data straight into your base. Under the hood it's a relational database with a friendly grid view, and its AI layer (Airtable AI) adds natural-language field generation, automatic summarization of long text fields, and the ability to ask questions about your base without writing a formula.
Airtable's real advantage isn't the AI — it's that the AI sits on top of data that's already structured correctly.
Where it fits best: teams tracking things with relationships — a content calendar linked to writers linked to clients, an inventory system linked to suppliers, a CRM linked to deals. If your "spreadsheet" has ever needed a VLOOKUP to work around the fact that it's really two tables pretending to be one, Airtable removes that pretending.
Where it falls short: raw numerical crunching. Airtable is built for structured records, not for running a regression or forecasting next quarter's revenue. For that, you'll want Obviously AI or Hex.
Rows: a spreadsheet that can call the internet
Rows starts from the opposite direction — it keeps the familiar grid and formula bar of a normal spreadsheet, then adds AI functions and live data connections directly into cells. You can write =AI("summarize this feedback") next to a column of survey responses, or pull live stock prices, social media metrics, or CRM data into a cell without exporting a CSV first.
The pitch here is continuity: nobody on your team has to relearn how a spreadsheet works. They just get new verbs to use inside cells they already understand — AI-generated text, AI-classified categories, AI-extracted entities — sitting next to the SUM and IF functions they already know.
Where it fits best: marketing and ops teams who live in spreadsheets daily and want AI as an added column, not a replacement tool. It's a strong pick if your team's objection to "AI data tools" has always been "I don't want to learn new software."
Where it falls short: it's still a spreadsheet at heart, so very large datasets (hundreds of thousands of rows) will strain it the same way they'd strain Google Sheets or Excel.
Formula Bot: the fastest fix for "what formula do I even need"
Formula Bot does one thing extremely well: you describe what you want in plain English — "give me the average of column B where column A says 'closed won'" — and it writes the exact Excel or Google Sheets formula for you, explained line by line. It also reads screenshots of spreadsheets and can debug a formula that's throwing an error.
This isn't a data-analysis platform in the way the other four are; it's closer to a formula translator that lives in your browser. But it solves a real and frequent bottleneck — the twenty minutes lost googling "how to do a nested IF with a VLOOKUP" — cheaply and immediately.
Where it fits best: anyone who works inside Excel or Google Sheets daily but isn't a power user of either. It's also genuinely useful as a learning tool, since it explains the formula rather than just handing it over.
Where it falls short: it doesn't restructure or analyze your data for you — it just gets you the formula. If the problem is your data model, not your formula knowledge, Formula Bot won't fix it.
Obviously AI: predictions without writing a model
Obviously AI connects to your spreadsheet or database and lets you build a predictive model — churn risk, demand forecasting, lead scoring — by picking a column to predict and clicking a button, no code and no data-science background required. It handles the messy parts (feature selection, model choice, validation) behind the scenes and returns a plain-English explanation of what's driving the prediction.
Obviously AI is aimed at the question spreadsheets are worst at answering: not "what happened" but "what's likely to happen next."
Where it fits best: small and mid-sized teams that want predictive analytics — the kind normally reserved for a dedicated data science hire — without justifying that hire. Sales teams scoring leads and ops teams forecasting demand are the two most common real-world uses.
Where it falls short: it's a prediction tool, not a general-purpose data workspace. For exploratory analysis, dashboards, or ad-hoc questions about your data, it's the wrong starting point — that's Hex's territory.
Hex: a notebook for people who don't want to write in a notebook
Hex is a collaborative data workspace built around notebooks — SQL and Python cells you can chain together — but its AI layer (Hex Magic) means you can prompt it in plain English to write the SQL query, generate the Python chart, or explain what a piece of existing code does. The output is a shareable, interactive report rather than a static spreadsheet export.
Where it fits best: teams that already have some technical depth (an analyst, a data-curious PM) and want to go beyond what a spreadsheet can show — joining multiple data sources, building an interactive dashboard non-technical stakeholders can filter themselves, or answering a one-off analytical question that would otherwise mean pinging the data team.
Where it falls short: it has a steeper learning curve than every other tool on this list. If your team has never touched SQL, the AI assistance narrows that gap but doesn't erase it.
Quick Comparison
| Tool | Best for | Skips the spreadsheet? | Learning curve |
|---|---|---|---|
| Airtable | Structured, relational data | No — reimagines it | Low-medium |
| Rows | AI inside a familiar spreadsheet | No | Very low |
| Formula Bot | Writing/fixing formulas fast | No | Very low |
| Obviously AI | No-code predictions and forecasting | Partially | Low |
| Hex | Deep analysis, dashboards, SQL/Python | Yes | Medium-high |
Frequently Asked Questions
Do I need to know SQL or Python to use any of these?
Not for Airtable, Rows, Formula Bot, or Obviously AI — all four are designed to be used entirely through plain English or a spreadsheet-style interface. Hex is the exception: its AI assistance writes SQL and Python for you, but you'll get more value from it if you can read and lightly edit what it produces.
Can I just use ChatGPT for this instead of a dedicated tool?
For a one-off formula or a quick explanation of a dataset you paste in, general chat assistants can help. Where they fall short is anything that needs to stay connected to live, structured data — a growing base of records, a dataset that updates daily, or a model that needs retraining as new data comes in. That's the gap these five tools are built to fill.
Which tool should a small business with no dedicated analyst pick?
Start with Airtable if the core need is organizing structured records (customers, inventory, projects), or Rows if the team already lives in spreadsheets and just wants AI assistance inside them. Obviously AI is worth adding once you have a specific prediction question — "which leads are likely to convert" — rather than a general organization problem.
Is Formula Bot worth paying for if I only use spreadsheets occasionally?
Its free tier covers most one-off formula requests, so it's worth trying before deciding whether to pay. The paid tier mainly pays for itself if you're building complex, multi-condition formulas regularly enough that the time saved adds up.
Final Verdict
There's no single winner here because these tools aren't really competing with each other — they're addressing different points along the same pipeline. Formula Bot fixes the formula in front of you right now. Rows and Airtable fix how your data is structured and displayed day to day. Obviously AI and Hex both go further, but in different directions: Obviously AI toward automated prediction, Hex toward flexible, code-backed analysis. The realistic path for most teams is starting with whichever tool matches today's bottleneck, not trying to adopt all five at once. For more AI-powered ways to handle the rest of your workday, browse the full Productivity & Data category.