Lead Magnets
What Is an Agentic Enrichment Spreadsheet?
Oct 30, 2026
Definition: An agentic enrichment spreadsheet is a spreadsheet where each column is an AI agent. You describe what a column should find, and the agent researches every row using data providers and the web, citing sources and leaving cells empty when nothing verifies.
Disclosure: Orange Slice, the publisher of this page, makes an agentic enrichment spreadsheet. We explain the category in general terms and say where other approaches fit better.
How an agentic enrichment spreadsheet works
A normal sales spreadsheet holds data someone typed or imported. An enrichment spreadsheet fills data in automatically. An agentic one goes further: each column has an instruction, and an AI agent carries it out row by row. The agent decides which provider to call, when to search the web, and what to do if a lookup fails.
Four ideas define the category:
- Columns are instructions, not formulas. "Find the person this role reports to" is a column. So is "Does this company sell to hospitals? Yes/No, with a source."
- Columns depend on each other. A buyer column needs the company domain first, and an email column needs the buyer. The sheet runs them in order.
- Waterfalls behind the scenes. For a contact detail, the agent tries several providers in turn and stops when one returns a verified result.
- Empty beats wrong. A good agentic sheet leaves a cell blank when there's no source, rather than guessing.
Orange Slice's YC company page describes its version as "a spreadsheet where every column is TypeScript—and AI writes it for you": you describe the column in chat, and it generates the code and runs it across thousands of rows.
Example: columns as agents
Say you sell sales-coaching software to B2B SaaS companies that are building an outbound team. Here's the sheet as five column instructions:
| Column | The agent's instruction |
|---|---|
| Careers page | Find the company's careers page or ATS job board |
| Trigger role | From postings in the last 30 days, list any SDR, BDR or first AE roles |
| Pain line | Quote one sentence from that posting that shows a sales problem |
| Buyer | Name, title and LinkedIn URL of the person the role reports to |
| Verified email | The buyer's work email, verified; empty if not found |
And here's what the rows might look like. Illustrative example data with made-up companies.
| Company (example) | Trigger role | Pain line | Buyer | Verified email |
|---|---|---|---|---|
| Example Ledger Co | First Account Executive | "Own the full cycle as our first AE" | CEO | found |
| Sample Ops Inc | 2× SDR | "Help us build outbound from scratch" | Head of Sales | found |
| Demo Analytics | none | — | — | — |
Notice the third row: no trigger, so the downstream columns stay empty. Nothing is invented. For the full version of this recipe, see how to find high-intent B2B prospects from job postings.
Agentic spreadsheet vs Clay tables vs AI SDRs
These three get mixed up, but they do different jobs.
| Agentic enrichment spreadsheet | Clay-style table | AI SDR | |
|---|---|---|---|
| What you do | Describe the list or column in plain language | Build the table column by column, choosing providers | Set goals and messaging; the tool prospects and sends |
| Output | A sheet of researched rows you review | A sheet of enriched rows you review | Sent emails and booked meetings |
| Human control | High: you see every cell and source before outreach | High: you design every step | Lower: the tool acts on your behalf |
| Learning curve | Low to start | Higher; very flexible once learned | Low to start, harder to tune |
| Best for | Signal-based lists, research-heavy targeting | Complex, custom workflows at scale | High-volume top-of-funnel |
Clay tables are the closest relative. Clay includes AI agents ("Claygents") inside its tables and a marketplace of 150+ providers (clay.com/pricing). The difference is mostly where you start: in Clay you design the table; in an agentic spreadsheet you describe the outcome and the agent designs the table. We go deeper in Orange Slice vs Clay.
AI SDRs automate sending as well as research. That's useful for volume, but you give up review of each row before it goes out. Many teams pair a research sheet with a sequencer they control. For a database-plus-sequencing approach, see Orange Slice vs Apollo, or the three-way Clay vs Apollo vs Orange Slice comparison.
When to use an agentic enrichment spreadsheet
It's a good fit when:
- Your targeting depends on research a database doesn't have, like "posted a first RevOps role," "mentions SOC 2 on their site," or "opened a new location."
- You want to review every row before outreach.
- You're a small team without a RevOps or GTM engineer to build workflows.
- You want lists that re-run on a schedule so new signals show up.
Something else may fit better when:
- You just need emails for a list of names. A lookup tool like Lusha or Apollo is simpler.
- You need years of historical job or tech data. Data providers like TheirStack or PredictLeads are built for that.
- You already have mature Clay workflows. Rebuilding them may not be worth it.
- You need a vendor with a SOC 2 report today. Check each vendor; Orange Slice doesn't have a SOC 2 audit yet (compare page).
See the full field in our list of Clay alternatives, or the startup angle in Clay alternative for YC startups.
What it costs
Pricing models vary across the category. Some tools charge platform credits plus data credits (Clay uses Actions and Data Credits). Others charge per lookup in dollars. Orange Slice, for example, has a Pay as you go plan at $0/month plus usage at vendor cost plus 25%, a Pro plan at $99/month with $50 of usage included, and an Agency plan at $499/month (pricing, checked Oct 30, 2026). Whatever the tool, compare the cost of a real run, including what happens on a miss, not just the plan price.
FAQ
What is an agentic enrichment spreadsheet?
It's a spreadsheet where each column is an AI agent. You describe what a column should find, such as a company's careers page, its buyer or a verified email. The agent then researches every row using data providers and the web. Good ones cite sources and leave cells empty instead of guessing.
How is it different from Clay?
Clay is a flexible table builder with a large provider marketplace and AI agents inside it; you design the table column by column. An agentic enrichment spreadsheet starts from a plain-language description, and the agent designs and runs the columns. Clay offers more control and providers; agentic sheets are faster to start.
Is an agentic enrichment spreadsheet the same as an AI SDR?
No. An agentic spreadsheet researches and structures data so you can review it before outreach. An AI SDR goes further and sends messages for you. Many teams prefer to research in a sheet and send through a sequencer they control, because they can check every row and source first.
What can the columns do?
Columns can find company details, careers pages, recent job postings, funding news, tech stack, decision-makers and verified contact details. They can also answer custom questions from the web, like whether a company serves hospitals. Each column depends on earlier ones, so the sheet runs them in order.
Who should use one?
They fit founders and small sales teams who sell based on timing signals like hiring, funding or new leaders, and who want to review every row before outreach. Teams that only need contact lookups or high-volume automated sending will often do better with a database tool or an AI SDR.
