Enrich leads before an AI agent writes personalized campaign copy

Give an AI SDR the person, company and hiring context it needs to write a message specific to each lead, and a verified address to send it to.

Get a free API key + $5 Get a sample run

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No credit card
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A selection of teams that run this job on Forager · plus other sales-tech platforms

Uses POST /person_detail_lookup/, POST /organization_search/, POST /job_search/ · Person enrichment API reference

What it costs: 5 credits per email found. A mobile or email lookup that returns nothing costs 0 credits. Enrichment and search are charged per request: credit pricing.

How the data flows

2 inputs → Person enrichment + Company enrichment + Work emails + Job postings API → 4 fields sample data

01 · Inputs

Your list

contacts.csv · 1,200 rows

LinkedIn URL

linkedin.com/in/priya-fixture

02 · Forager

Person enrichment + Company enrichment + Work emails + Job postings API POST /person_detail_lookup/

Match found

03 · Outputs

Priya FixtureVP Revenue Operations · Example Inc.

company context: Example Inc.
open roles: VP Revenue Operations
work email: priya@example.com
name: Priya Fixture
mobile: +44 20 7946 0958

4 fields in the responseexample data

Steps

Enrich each lead with POST /person_detail_lookup/ (role history, tenure, location)
Add company context with POST /organization_search/ and recent hiring from POST /job_search/
Fetch work_email from /person_contacts_lookup/work_emails/ and drop leads with no deliverable address
Pass the structured context to the LLM prompt and log reply rate by context used

import json, os, requests

BASE = "https://api-v2.forager.ai/api/{account_id}/datastorage"
HEADERS = {"X-API-KEY": os.environ["FORAGER_KEY"]}
body = json.load(open("request.json"))  # request fields: see the API reference

# 1. Enrich each lead with POST /person_detail_lookup/ (role history,
# tenure, location)
r1 = requests.post(f"{BASE}/person_detail_lookup/", headers=HEADERS, json=body)

# 2. Add company context with POST /organization_search/ and recent hiring
# from POST /job_search/
r2 = requests.post(f"{BASE}/organization_search/", headers=HEADERS, json=body)
r3 = requests.post(f"{BASE}/job_search/", headers=HEADERS, json=body)

# 3. Fetch work_email from /person_contacts_lookup/work_emails/ and drop
# leads with no deliverable address

# 4. Pass the structured context to the LLM prompt and log reply rate by
# context used

# 1. POST /person_detail_lookup/
curl -X POST \
  https://api-v2.forager.ai/api/{account_id}/datastorage/person_detail_lookup/ \
  -H "X-API-KEY: $FORAGER_KEY" \
  -H "Content-Type: application/json" \
  -d @request.json

# 2. POST /organization_search/
curl -X POST \
  https://api-v2.forager.ai/api/{account_id}/datastorage/organization_search/ \
  -H "X-API-KEY: $FORAGER_KEY" \
  -H "Content-Type: application/json" \
  -d @request.json

# 3. POST /job_search/
curl -X POST \
  https://api-v2.forager.ai/api/{account_id}/datastorage/job_search/ \
  -H "X-API-KEY: $FORAGER_KEY" \
  -H "Content-Type: application/json" \
  -d @request.json

Generated from the recipe stepsRequest fields: API reference

Run it yourself: Person enrichment API reference

Get a free API key + $5 Get a sample run

Free API key
No credit card
Run your sample

Inputs and outputs

Inputs	Outputs
lead list	`person context`
profile URL or name + company	`company context`
	`open roles`
	`work_email`

Questions about this recipe

What data should an AI SDR have about a lead before writing an email?

You send lead list and profile URL or name + company. You get back person context, company context, open roles and work_email. AI-written emails cite real facts about the lead and get more positive replies.

What does it cost to enrich leads before an AI agent writes personalized campaign copy?

Person enrichment: 1 credit per request, charged whether or not data comes back. Company enrichment: 1 credit per request, charged whether or not data comes back. Work emails: 5 credits per work email found, and a work email lookup that finds nothing costs 0 credits. Job postings API: 2 credits per request, charged whether or not data comes back. Growth's 8,250 monthly credits cover 1,650 emails or 8,250 person enrichments, or a mix. Self-serve plans are Starter, Growth, Pro and Scale. See plans and prices

What do I need to run this recipe, and what comes back?

You send lead list and profile URL or name + company. You get back company context, open roles, person context and work_email, as JSON. You also need a Forager API key, which comes with a free account.

How do AI sales agents personalize cold emails at scale?

Enrich each lead with POST /person_detail_lookup/ (role history, tenure, location). Fetch work_email from /person_contacts_lookup/work_emails/ and drop leads with no deliverable address.

Is there a free way to try Forager on this workflow?

Yes. Create a free account at app.forager.ai: it comes with $5 in free credits and an API key, and there is no credit card to sign up. Run it on records you already know, or book a demo and send us a list: we run it and show you what we find.

When should I run this workflow?

When a user uploads a lead list or the agent builds one and queues a campaign. AI-written emails cite real facts about the lead and get more positive replies.

Which Forager products does this recipe use?

Person enrichment, company enrichment, work emails and job postings API. Person enrichment: a full professional profile for a person from a LinkedIn URL, email or phone: experience, education, skills and contact channels. Company enrichment: firmographics for a company from its domain or name: industry, headcount, locations, growth and open roles.

How accurate is Forager data?

The test that counts is your own: send a list of profiles you care about. We run it and show you what we find, number by number, so you can measure hit rate and connect rate yourself.

How do I enrich leads for AI SDR personalization?

Enrich each lead with POST /person_detail_lookup/ (role history, tenure, location). Fetch work_email from /person_contacts_lookup/work_emails/ and drop leads with no deliverable address.

Which tools can run this workflow?

Native in Clay and Zapier, partner-built in Deepline and Cargo and called through the API from Make, n8n and your own code. Or call the endpoints in the steps above from your own code with one API key.

How many steps is this workflow?

4 steps: enrich each lead with POST /person_detail_lookup/ (role history, tenure, location), add company context with POST /organization_search/ and recent hiring from POST /job_search/, fetch work_email from /person_contacts_lookup/work_emails/ and drop leads with no deliverable address and pass the structured context to the LLM prompt and log reply rate by context used.

Is there a contract or minimum commitment?

No contract to start: a free account comes with $5 in credits. To keep using Forager, choose a monthly or yearly plan. Monthly plans cancel anytime and unused credits roll over; yearly plans grant all credits upfront and cost 10% less. Larger volumes are agreed with our team.

A selection of teams that run this job on Forager · plus other sales-tech platforms

Clay
- GTM workflow builders
Selected use case: Forager mobile numbers, emails and people data inside Clay tables.
Juicebox
- AI candidate sourcing
Selected use case: Forager data behind its PeopleGPT search and sourcing agents.
Nooks
- Power & parallel dialers
Selected use case: mobile numbers inside their dialer.
Roger
- AI SDRs
AI outbound sales rep.
Amplemarket
- AI SDRs
Selected use case: mobile numbers inside its contact waterfall.
HubSpot
- CRM add-ons
Selected use case: enriching contact and company records with people, company and job-posting data.
Jeeva AI
- AI SDRs
Agentic platform of AI digital workers for sales teams.
Orbital
- Lead databases
Selected use case: contact lookups in its enrichment waterfall, for teams selling to local businesses.

Enrich leads before an AI agent writes personalized campaign copy

How the data flows

Steps

Inputs and outputs

Questions about this recipe

What data should an AI SDR have about a lead before writing an email?

What does it cost to enrich leads before an AI agent writes personalized campaign copy?

What do I need to run this recipe, and what comes back?

How do AI sales agents personalize cold emails at scale?

Is there a free way to try Forager on this workflow?

When should I run this workflow?

Which Forager products does this recipe use?

How accurate is Forager data?

How do I enrich leads for AI SDR personalization?

Which tools can run this workflow?

How many steps is this workflow?

Is there a contract or minimum commitment?

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