AI ICP-fit research and routing

High-intent inbound leads get researched, scored against your ideal customer profile, and routed to a rep only when they clear the bar.

High-intent inbound leads get researched, scored against your ideal customer profile, and routed to a rep only when they clear the bar. A high-intent lead is one that shows real buying interest, such as a demo request or a pricing-page visit. This recipe fires on Record added to list. It then runs a read-only Web agent behind a free Filter. Research only runs on companies that clear your ideal customer profile (ICP) threshold. Your ICP is the kind of company you most want to sell to. From there, Classify record assigns an A, B, or C fit band. Switch branches on that band, and Update record saves the research. The recipe then assigns qualified leads with Round robin and notifies the owner with a Slack message.

Difficulty	Advanced
Time to build	~25 minutes
Trigger	Record added to list, or Webhook received
Blocks used	Filter, Web agent, Classify record, Switch, Update record, Round robin, Slack
Credit cost per run	Variable. The Web agent is token-based, and each write costs 1 credit. See Credits & pricing explained
Plan required	Pro recommended

Prerequisites

• An Attio plan that includes the agent and AI blocks. Pro is recommended for the volume this recipe assumes. Confirm current plan availability on Credits & pricing explained.
• The Slack integration connected to your workspace, with the workflow authorized to post in your routing channel.
• A list for high-intent inbound leads. For example, a list named Inbound: high intent that a form, a product event, or a routing rule adds leads to.
• Three attributes on the Companies object. Add a long-text attribute for the research summary (slug icp_research). Add a single-select attribute for the fit band (slug fit_band, with options A, B, and C). Add an owner attribute (slug owner).
• A read-only Run as identity for the Web agent. The agent reads records and the public web but cannot write back. See Permissions & workflow access.

How it works

The trigger fires the moment a lead enters the high-intent list. A free Filter checks the lead against your ICP threshold and stops the run when it does not qualify. This means the token-priced Web agent never touches raw, low-fit traffic. Each qualifying company reaches the Web agent, which answers two to four specific qualification questions read-only.

Classify record turns that research into an A, B, or C fit band. A Switch then branches on the band. Update record saves the summary and band to the company. Round robin assigns an owner to A and B leads, and a Slack message notifies that owner.

The blocks run in this order:

1. Record added to list: a high-intent lead enters the list.
2. Filter: continue only when the lead clears the ICP threshold. The run stops otherwise.
3. Web agent: research the company read-only against two to four qualification questions.
4. Classify record: assign an A, B, or C fit band from the research.
5. Switch: branch on the fit band.
6. Update record: save the research summary and band to the company.
7. Round robin: assign an owner to A and B leads only.
8. Slack: notify the assigned owner.

Build steps

1. Add the trigger

   Create a new workflow. Click the Add trigger button, choose Record added to list, and select your high-intent inbound list. If your leads arrive from an external form or product event, use Webhook received instead. In that case, resolve the payload to a company record before the Filter.

   Field	Value
   Trigger	Record added to list
   List	Inbound: high intent
   Object	Companies

2. Gate the agent with a Filter

   Add a Filter immediately after the trigger. The Filter is the cost guard. It is free, and it stops every below-threshold run before the Web agent spends a token. Set conditions that approximate your ICP.

   Field	Value
   Block	Filter
   Condition 1	domain is not empty
   Condition 2	employee_count is greater than 50
   Condition 3	region is one of EMEA, North America
   Match	All conditions

   Place the Filter before the Web agent, not after. The Web agent is token-priced, so a Filter that sits downstream spends credits on leads you intended to skip.

3. Research with a read-only Web agent

   Add a Web agent after the Filter. Set its Run as identity to a read-only research user. The agent then reads the record and the public web but cannot write back. Keep the prompt to two to four specific questions.

   Field	Value
   Block	Web agent
   Run as	Research (read-only)
   Input	acme.com (from domain)
   Questions	What does this company sell? Who is the likely buyer? Why might they need our product now? What is a relevant first line for outreach?

   Use a tightly scoped prompt so the agent returns structured, verifiable research:

   Research this company for a B2B sales rep. Return:
   1. one-sentence company summary
   2. likely business model
   3. why they may have urgency now
   4. one concise outreach angle
   
   Avoid unsupported claims. If you cannot verify something, say so.
   
4. Classify into fit bands

   Add a Classify record block. Feed it the company record plus the agent’s research, and have it return a single fit band.

   Field	Value
   Block	Classify record
   Input	{{ web_agent.summary }} plus company attributes
   Categories	A is strong ICP fit; B is partial fit; C is weak or out of ICP
   Output	fit_band

5. Branch on the band with a Switch

   Add a Switch on the fit band so A and B leads get routed and C leads are saved but not assigned.

   Field	Value
   Block	Switch
   Switch on	{{ classify_record.fit_band }}
   Case A	Save, assign, notify
   Case B	Save, assign, notify
   Case C	Save only

6. Save the research

   Add an Update record block in every branch to write the research and band back to the company. The Web agent does not save anything on its own.

   Field	Value
   Block	Update record
   Record	Trigger company
   icp_research	{{ web_agent.summary }}
   fit_band	{{ classify_record.fit_band }}

7. Assign qualified leads with Round robin

   Add a Round robin block in the A and B branches only. It picks the next rep and writes the owner.

   Field	Value
   Block	Round robin
   Pool	EMEA AEs: Priya Sharma, Jordan Lee, Mateo Ruiz
   Assign to	owner

8. Notify the owner over Slack

   Add a Slack block in the A and B branches to message the assigned rep.

   Field	Value
   Block	Slack
   Channel or user	Assigned owner from Round robin
   Message	New {{ fit_band }} lead: {{ company.name }} ({{ domain }}). Research saved in Attio. Owner: {{ owner }}.

Variable mapping

Variable	Source block	Field	Example value
domain	Trigger	Company domain	acme.com
web_agent.summary	Web agent	Research output	”Acme sells warehouse robotics to mid-market 3PLs…”
classify_record.fit_band	Classify record	Category	A
owner	Round robin	Assigned rep	Priya Sharma
company.name	Trigger	Company name	Acme Robotics

Credit cost worked example

Assume 400 leads enter the high-intent list each month, and the ICP Filter passes about 30% of them (120 leads). The Filter, Switch, and Round robin are free logic blocks. The token-based cost of this recipe is the Web agent, plus Classify record and the writes.

• Filter: free, runs on all 400 leads.
• Web agent: variable and token-based. It runs only on the ~120 leads that pass the Filter. Do not assume a fixed number. Sample about 10 representative leads, run them, and read the actual per-run credit cost in the run viewer before you scale. Gating with the Filter is what keeps this line from running on all 400.
• Classify record: variable and token-based, about 120 runs. Sample and read the per-run cost the same way.
• Update record: 1 credit each, about 120 runs.
• Round robin: free, A and B leads only.
• Slack: 1 credit each, A and B leads only.

So the fixed-rate floor is roughly 120 Update writes plus one Slack message per assigned A or B lead. The variable ceiling is the Web agent and Classify record totals you measure in the run viewer. Compare that monthly total against your plan allowance on Credits & pricing explained.

Per-workflow credit caps were removed in the new engine, so the Filter is your spend control. There is no cap to fall back on. The tighter the Filter, the fewer leads reach the token-based blocks.

Test plan

1. Add a real ICP-fit company to the high-intent list to fire the trigger. For example, use a 200-person EMEA SaaS firm with a populated domain.
2. Open the run in run history and confirm the Filter passed. Expect a green continue.
3. Confirm the Web agent returned a research summary keyed to your four questions, and that its Run as identity is read-only.
4. Confirm Classify record output an A, B, or C band.
5. Confirm the Switch entered the matching branch, and that Update record wrote icp_research and fit_band to the company. For A and B, also confirm that Round robin set an owner and Slack posted to that owner.
6. Now add a deliberately failing input: a lead with an empty domain and an employee_count of 5. Expect the Filter to stop the run before the Web agent. Verify in run history that no agent or write block executed and that no tokens were spent.

Failure modes

Symptom	Cause	Fix
Credit spend far higher than expected	The Web agent runs on raw, low-fit leads	Tighten the Filter, confirm it sits before the Web agent, and re-sample 10 runs in the run viewer.
The research summary is blank in Attio	No Update record follows the agent	Agent output is not saved automatically. Add Update record mapping {{ web_agent.summary }} into icp_research.
The agent attempts to write, or errors on permissions	The Run as identity has write access or is the wrong user	Set the Web agent’s Run as to a read-only research user.
C leads get assigned and pinged	Round robin and Slack sit outside the Switch	Move Round robin and Slack into the A and B branches only.
The owner field stays unset on qualified leads	The Round robin pool is empty or not mapped to owner	Populate the pool and map the assigned rep to the owner attribute.
Webhook leads never trigger	The payload is not resolved to a company record	When using Webhook received, create or match the company before the Filter.

Variations

Command trigger to control spend

Swap Record added to list for Record command so a human chooses when a lead is worth researching. Everything downstream stays identical. This puts the token-priced Web agent behind an explicit click instead of an automatic list event. That is the safest way to cap spend while you tune the Filter.

Summarize record for a cheaper tier

For high volume, or for B-tier leads where public-web research is not worth the cost, replace the Web agent with Summarize record. It is still token-based, but it works only from data already in Attio with no web browsing. That means it costs less per run. Keep the Filter, Classify record, Switch, and routing unchanged. Only the research block changes.

See also

• AI agents playbook
• Permissions & workflow access
• Web agent
• Classify record
• Credits & pricing explained

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Sources: Attio Workflows block library, Manage workspace and seat credits. Last reviewed against the Attio Help Center, June 2026.