I replaced a $400/mo enrichment tool with one Attio Research attribute

The team I was helping had a Clay seat at $185 a month, a Clearbit credit pack at around $200 a month, and a Zapier line item to push the data into HubSpot. They were paying close to $400 a month to enrich about 250 inbound companies. Half the fields they were paying for were never read again.

I turned off both tools and replaced the workflow with a single Attio Research attribute. One field on the Companies object. Six lines of prompt. Twelve real outputs in the first hour, one hallucination caught on the fourth, and a credit bill that came in under $10 for the month.

This is the walk-through. The exact prompt, the field config, three real outputs, the one I caught wrong, and the cost math at the bottom.

What an Attio Research attribute actually is

A Research attribute is a field on a record. The value is generated by an AI model that searches the web, scoped to a question you write, and writes a structured answer back into the field.

Four things matter about how it sits in the data model.

1. It is a real field. Views, filters, automations, the API, and the MCP server treat it the same as any text field. You can sort, filter, and branch on the value with no glue.
2. It runs on triggers, not on a schedule. New record, attribute change, automation step. You decide when it fires. There is no nightly recompute eating credits in the background.
3. It uses variables. You can reference any other attribute on the same record or on a linked record inside the prompt. The same prompt works for Acme Corp and for a 200-person fintech in Singapore because the variables fill in the specifics.
4. It costs 10 credits per run. That is one number. Easier to budget than a Clay action graph or a Clearbit credit pack that expires every 30 days.

Most teams know AI Attributes exist. Far fewer have written a Research attribute that actually replaces a paid tool. The gap is in the prompt.

The exact prompt

Here is the prompt running on the Companies object in the workspace I rebuilt. Copy it, change the variables, ship it.

You are a B2B research analyst.

Research the company {{company_name}} (domain: {{domain}}).

Return six fields, in this exact order, separated by " | ":
1. One-sentence description of what they sell.
2. Most recent funding round (stage, amount in USD, date in YYYY-MM).
3. Approximate headcount band: 1-10, 11-50, 51-200, 201-500, 501-1000, 1000+.
4. Primary buyer persona (the role most likely to buy a CRM).
5. Two named, current competitors.
6. One concrete buying signal in the last 90 days (hire, launch, raise,
   acquisition, layoff, expansion). Include the date.

Source rule: only use information dated in the last 18 months.
If you cannot find a field with confidence, write "unknown" for that field.
Do not guess. Do not paraphrase older information into a recent date.

Six fields. One delimiter. Hard "unknown" fallback. That last rule is the one most teams skip and the one that catches the hallucinations.

The field config

Configuration in Attio takes about 90 seconds.

• Object: Companies.
• Attribute type: AI Research.
• Name: Research brief.
• Description: Used by automations and views. Refreshes on new record creation only.
• Prompt: the block above.
• Variables in prompt: {{company_name}} and {{domain}}, both already on the Company record.
• Trigger: automation step "When a Company is created, run this attribute." No global recompute.
• Format: plain text (the model returns the pipe-delimited string, automations parse it).

Two settings are not obvious and worth setting on the first pass.

Refresh trigger. If you let the Research attribute re-run every time any field on the company changes, you will burn 10 credits every time a rep moves a deal. Pin it to "create only" or to a deliberate trigger like "when ICP segment is set."

Source rule. "Only use information dated in the last 18 months" cuts the most common hallucination shape: the model confidently recycling a five-year-old funding round and dating it last quarter. The 18-month frame forces it to either find recent evidence or return "unknown."

Three real outputs

Three companies the attribute was run against in the first batch. Domains and names changed, structure preserved.

Company A: a developer tools company in Berlin

A self-serve API monitoring product for backend engineering teams |
Series A, $14M USD, 2025-07 |
51-200 |
Head of Engineering |
Datadog, New Relic |
Hired a new Head of Sales (2026-03)

Useful row. Funding round date checked out against the company's own blog. Competitors named the two we expected. The buying signal at the end is the one a rep can actually open with.

Company B: a fintech in São Paulo

A B2B accounts payable automation platform for mid-market Brazilian companies |
Seed, $4.5M USD, 2024-11 |
11-50 |
CFO |
unknown, unknown |
Launched a new AP module for Mexico (2026-02)

The "unknown" on competitors is a feature, not a bug. The model could not name two with confidence, so it said so. That is the prompt working as designed.

Company C: a US-based logistics SaaS

A last-mile delivery routing platform for retail chains |
Series B, $32M USD, 2025-11 |
201-500 |
VP Operations |
Onfleet, Bringg |
Acquired a smaller routing engine startup (2026-01)

Clean. The acquisition signal is the kind of detail a rep would otherwise spend 20 minutes on LinkedIn to find.

The hallucination on Company D

This is the one that matters. The fourth company in the batch came back with a funding round that did not exist.

A vertical SaaS for veterinary clinics |
Series A, $11M USD, 2025-09 |
51-200 |
Practice Owner |
unknown |
Expanded into Canada (2026-01)

The Series A date and amount were confidently wrong. The company had raised a Seed round in 2023 and nothing since. The "expanded into Canada" buying signal was real (their site had a Canadian pricing page added in January). The funding number was not.

How I caught it: the next step in the automation pipes the brief into a Slack channel for the AE. The AE who owns the vet vertical knew the company personally. He flagged it the same morning.

How to catch this kind of thing without a human in the loop: a second attribute, cheaper, that does one thing.

Verify {{research_brief}} against the company's own website {{domain}}.
For the funding round line, return one of: "verified", "contradicted",
"not found".

That is a Prompt Completion attribute, 1 credit per run. It runs after the Research attribute and writes a small verification flag. Anything contradicted gets routed to a "needs review" view. The Research brief stays the source of speed. The Prompt Completion stays the source of trust.

This two-attribute pattern is the answer most teams looking for an "anti-hallucination prompt" actually need. There is no such prompt. There is only a verifier.

What this costs

This is the part that makes the case obvious.

Clay, current pricing as of March 2026

A fully enriched record on Clay typically consumes 6 to 20 data credits. On the Launch plan, 2,500 credits gets you between 125 and 400 enriched records before you hit the cap. For 250 records a month at the higher cost end, the Launch plan is tight and the Growth plan is the only safe pick. Source: Clay pricing breakdown 2026.

Clearbit / Breeze Intelligence after the HubSpot acquisition

Standalone Clearbit is being sunset. To use Breeze Intelligence in 2026 you need a paid HubSpot subscription plus credits, and credits expire monthly with no rollover. Sources: Cleanlist, MarketBetter.

Attio AI credits, same job

A Research attribute consumes 10 credits per run. A Classify, Summarize, or Prompt Completion attribute consumes 1 credit per run. The Pro plan's 10,000 credits cover roughly 1,000 Research runs a month, or 10,000 cheap-attribute runs, or any mix. Source: Attio pricing.

The math on 250 enriched records a month

Even if the team needed two Pro seats to spread the credit ceiling, that is $138 a month. The Clay or Clearbit stack costs three to seven times more for the same enrichment job.

The savings are not the headline. The headline is that the data lives in the same record the rep already opens, the same workflow already branches on, the same view already filters by. No sync, no Zapier, no field-mapping drift.

When this beats Clay and when it doesn't

Honest version. The Research attribute is not a Clay replacement for everyone.

The Research attribute wins when:

• The job is web research and structured fields, not verified contact data.
• Volume is under a few thousand records a month.
• The fields you need are already shaped like CRM attributes, not like a 40-column waterfall.
• The downstream workflow (routing, scoring, sequencing) already lives in Attio.
• A 90-second prompt edit is faster for your team than a Clay table rebuild.

Clay still wins when:

• You need verified phone numbers and validated emails. Attio's Research attribute does web research, not waterfall enrichment across 150 paid data providers.
• You are running 5,000+ enrichments a month with high data variance.
• You need intent signals across browser activity, hiring, and tech stacks at the kind of depth Clay built specifically for.
• Your GTM is sourcing-led. Attio is built for managing customers and pipeline. Clay is built for finding new ones at the top of the funnel.

A useful rule of thumb: Clay is for sourcing, Attio is for everything that happens after the record exists. Many teams keep Clay for the sourcing layer and rely on Attio Research attributes for everything inside the CRM. The $400/mo replacement happens when you realize the company was using Clay for the second job, not the first.

Five Research attributes worth shipping in week one

Once the first one works, the templates compound. These five are the ones that pay for themselves before the credit pack runs out.

1. Research brief (the one above). Six fields per company. Replaces the manual lookup before the first reply.
2. ICP fit reasoning. Take the segment your Classify attribute picked, and ask the Research attribute to write the one-line "why this segment" justification. Useful for sales handoffs and quarterly pipeline reviews.
3. Buying signal radar. Run weekly on every open opportunity. Returns the single most relevant news item from the last 30 days. Drops into the deal record.
4. Stakeholder map. On the People object, run once per new contact: their current role, their predecessor, the team they sit on, and one peer name. Replaces the LinkedIn tab a rep keeps open during the call.
5. Account refresh. Quarterly recurring on every account. Returns "what changed in the last 90 days" in three bullets. Replaces the QBR prep document.

Each one is the same shape. Tight prompt. Variables from the record. Hard "unknown" fallback. Verifier attribute downstream when accuracy matters.

What this means if you are still paying for Clay or Clearbit

Three quick checks before you cancel anything.

One. Pull the last three months of Clay or Clearbit usage. Group by what the data was actually used for. If 70% or more was research and structured fields, the Attio Research attribute will replace it for less.

Two. Try the prompt above on five companies in your workspace. Compare the output to what your enrichment tool returned for the same companies. If the Research attribute output is close enough to drive the same downstream decisions, the gap is closed.

Three. Build the verifier attribute alongside the research one. The hallucination on Company D is not unusual. The hallucination not being caught is unusual, and only because a rep happened to know the company. The two-attribute pattern catches it without depending on a person.

If all three checks pass, the migration is one afternoon. Turn off the enrichment tool, freeze the credits, point the inbound automation at the new Research attribute, and watch the Slack channel for two weeks.

Sources

• Attio: AI attributes documentation
• Attio: Introducing the AI-powered Research Agent
• Attio: Pricing
• Salesmotion: Clay pricing breakdown 2026
• Cleanlist: Clearbit pricing guide 2026
• MarketBetter: Clearbit pricing breakdown 2026
• novlini: Attio + Clay CRM enrichment

Free audit of your Attio workspace

If you want a second pair of eyes on whether your enrichment stack can collapse into Attio, I run a free 48-hour audit. You add me as an Attio expert, no extra seat and no billing. I send back a one-page teardown ranked by impact, the three highest-leverage Research attributes to ship first, and a 5-minute Loom walking through the top one. No call, no pitch. 5 slots a week.

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