Do I need to know how to code?

No. You describe the workflow in plain English—what to enrich, where to pull the input list from, and where to write the results. Twin builds and runs the agent from that description.

Can my FullEnrich agent run on a schedule?

Yes. You can configure an agent to run daily, hourly, or on any recurring schedule. For example, the Prospect Research & Outreach agent searches LinkedIn and enriches contacts every day without manual triggering.

What other tools can I combine with FullEnrich?

Google Sheets is the most common pairing—agents typically read input domains from a sheet and write enriched records back. CRM tools like Attio are also used to keep pipeline data current after enrichment runs.

What kinds of records can Twin enrich through FullEnrich?

Agents can enrich contacts, companies, and role-specific records. Existing agents cover CTOs, paid users, real estate leads, and competitor contacts—all using FullEnrich to resolve verified email addresses.

Which FullEnrich agents in the Twin community can I clone?

The FullEnrich agents section above lists the most-run community builds, with run and clone counts on each card so you can pick a battle-tested starting point. Cloning is faster than starting empty and the agent comes pre-wired to FullEnrich.

Integration

Automate FullEnrich for your team

Build agents that enrich prospect domains, pull verified contact emails, and push results to your CRM or spreadsheet—on a schedule or on demand.

Automate FullEnrich Browse 8 FullEnrich agents

Integration guide

How Twin uses FullEnrich inside repeatable agent workflows

Twin treats FullEnrich as part of a larger workflow, not as an isolated connector. An agent can read the relevant records, combine them with context from other tools, decide what needs to happen next, and report the finished work back to the team.

The page below shows the practical automation patterns for FullEnrich: what the agent can monitor, which actions it can take, and how the workflow stays observable when it runs on a schedule.

Common starting points include lead enrichment, sales prospecting, crm automation. Each example is designed to become a reusable agent, so teams can start from a narrow job and expand it as the process matures.

Twin is most useful when manual copying between FullEnrich and your CRM or spreadsheet creates stale data and missed follow-ups. Twin turns the workflow into an agent that runs on a schedule without intervention.

What you can do with FullEnrich

Real FullEnrich workflows the Twin community runs every day, ready for you to clone.

Enrich prospect domains at scale

Submit a list of company domains to FullEnrich and retrieve verified contact emails for each, then export the updated records automatically.
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Daily LinkedIn prospect discovery

Search LinkedIn for target companies each day, identify a relevant contact per company, and use FullEnrich to resolve their email address.
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Enrich paid users or CRM records

Pull existing contact or company records, send them through FullEnrich for enrichment, and write the results back to your source system.
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Competitor contact enrichment

Given a list of competitor companies, find relevant contacts and enrich their details via FullEnrich for competitive intelligence or outreach.
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Sync enriched data to Google Sheets

After enrichment runs, write contacts, companies, and lead status fields directly into a Google Sheet for review or downstream use.
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Role-specific contact enrichment

Target specific roles—like CTOs—across a list of companies, enrich contact details through FullEnrich, and surface results for outreach.
Explore

How it works

Three steps from idea to a running FullEnrich agent.

1

Connect via OAuth

Sign in to FullEnrich once. Twin securely manages the connection and handles token refreshes for you.
2

Describe the workflow

Tell Twin in plain English what you want done in FullEnrich. The agent figures out the API calls itself.
3

Twin builds and runs

Twin assembles the agent, runs it on demand or on a schedule, and adapts when FullEnrich responds in unexpected ways.

Why Twin for FullEnrich

What makes Twin a better fit than a generic automation tool.

Repeatable, not one-off

Manual copying between FullEnrich and your CRM or spreadsheet creates stale data and missed follow-ups. Twin turns the workflow into an agent that runs on a schedule without intervention.

Works with what you connect

FullEnrich workflows may involve API calls, browser steps, or both depending on your setup. Twin can use whichever access method is available and handle the handoff between tools automatically.

Pairs with your existing stack

The most common Twin agents combine FullEnrich with Google Sheets and CRM tools. You describe the workflow once; Twin handles the sequencing across all connected apps.

FullEnrich agents from the community

8 community-built agents touch FullEnrich. The most-run ones are below — clone any of them in one click.

AI employee

Funding Round Tracker

Read the LOOKBACK window and pull the list of funding announcements published in that window from each configured source

Parse each announcement into structured fields: company, website, round stage, round amount USD, announcement date, lead investor, brief description

Drop rounds that fall outside the configured stage filter, round-size band, geography, or ICP industries

For every surviving company, find the founder/CEO plus one go-to-market decision maker matching the configured target titles

Enrich each contact with verified work email and LinkedIn URL, scoring deliverability confidence

+3 more steps

8 Uses

AI employee

Talent & Role Scout

Load every previously processed item_id from the agent database for deduplication.

Generate platform-specific queries from the target profile, locations, and industry focus, then run them through Scrape Platforms, Web Search, and Deep Research.

Use Twin AI to normalize raw scrape output into structured items with title, organization, location, URL, and source.

Discard items missing a canonical URL or matching an exclusion keyword, then drop any item_id already seen.

Score remaining items 0 to 100 against the target profile and keep those above the relevance threshold.

+3 more steps

4 Uses

AI employee

Prospect List Builder

At run start, query the internal leads table to load every previously surfaced identifier

Expand the ICP into 8-12 targeted search variants across Google Maps, LinkedIn, and web search

Run scrapers and searches in parallel, then merge results into a single candidate list

Drop any candidate whose key (email or domain) is already in the database

Optionally enrich each remaining candidate with owner/contact details via web research

+3 more steps

67 Uses

AI employee

Advisor & Firm Prospect Hunter

Load previously discovered firms from the agent database into a deduplication set

Run parallel searches across selected source platforms using ICP-derived keywords and filters

Score each candidate against vertical-focus criteria and drop near-duplicates

Enrich qualified firms with role, location, and contact details

Append new firms to the Google Sheet and update enrichment status

+2 more steps

9 Uses

AI employee

ICP Deal Triager

Trigger: poll the CRM for deals created or updated since the last successful run

For each new deal, look up the associated company and contacts, then run deep research on the domain (site, recent press, funding, headcount, stack signals)

Score the deal against the ICP rubric across configured dimensions and store the score plus rationale in the agent database

If score is below the rejection threshold, update the deal stage to the rejection stage and log a one-line reason in the deal notes

If score is at or above the brief threshold, draft a pre-call brief (company snapshot, fit score breakdown, angle, risks, suggested questions) and email it to the configured recipient

+2 more steps

2 Uses

AI employee

Open Deal Contact Enricher

Query the CRM for contacts on deals in active pipeline stages that are missing the selected enrichment fields

Drop any contact already attempted in the past 30 days (looked up in the agent database)

Chunk the remaining contacts into batches and submit each batch to the enrichment vendor

Poll the vendor until each batch finishes, then map results back to CRM contact IDs

For each result: if confidence meets the threshold, write the verified field(s) back to the CRM; otherwise apply the low-confidence action

+3 more steps

3 Uses

AI employee

Job Insider Intel Composer

User pastes a job posting URL (or raw JD text) and the agent ticks immediately.

Agent scrapes and validates the posting, confirming it's still active and capturing JD fields into a typed structure.

Agent runs company research in parallel: recent news, funding, leadership changes, layoffs, product launches, Glassdoor-style signals.

Agent identifies the hiring manager and skip-level by mapping the role to the org chart, then enriches each with a verified work email via the connected enrichment app.

Agent extracts verbatim interview-ready phrases from the JD and public collateral, mapped to expected interview themes.

+2 more steps

8 Uses

AI employee

ICP Lead Hunter

Pulls previously surfaced lead URLs from the agent database to avoid repeats

Runs parallel platform scrapes filtered to the last 24 hours using your ICP keywords

Filters out ads, off-topic posts, resolved threads, and out-of-region results

Scores remaining leads on keyword fit, seniority, recency, and engagement

Writes new leads to the agent database and, if connected, to your CRM or sheet

+2 more steps

153 Uses

AI employee

LinkedIn Talent Sourcer

Wake on the configured cadence and load role profile, skill keywords, location filter, and result cap from the agent state

Open the sourcing platform via Browser Agent or Scrape Platforms, apply skill + location filters, and collect candidate cards up to the per-run cap times 3 to allow for dedupe loss

For each candidate, normalize a stable profile_key (slug of profile URL) and check the sourced-candidate database for any match within the dedupe window

Use Twin AI to score remaining candidates against the role profile, attaching a 1-5 fit score and one-line fit reason

Optionally call the enrichment provider in parallel to attach a business email and verified company domain

+3 more steps

5 Uses

Common FullEnrich use cases

Patterns that show up across the Twin community — start from one and adapt it.

Lead enrichment

Turn sparse lead records into usable context for outreach.

See use case

Sales prospecting

Find, enrich, and prioritize prospects from web and app data.

See use case

CRM automation

Update records, create tasks, and keep pipelines current.

See use case

Competitive research

Monitor competitors and summarize changes.

See use case

Build with more than FullEnrich

These related integration pages give crawlers and readers another path through the automation catalog. They connect FullEnrich to nearby apps, categories, and paired workflows that teams often evaluate together.

See all integrations