Use case · LinkedIn automation

LinkedIn outreach that does not get flagged.

Connections, messages and follow-ups across as many accounts as you run, with warm-up and health-aware limits enforced server-side, before every action. 80% of automation users get restricted in their first year; this stack is built so you are not one of them.

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LinkedIn accounts2,418 connectedscroll →

Account	Status	Anti-detect browser	Proxy	Geo	Daily limit	Acceptance	Health	Last active
Emily Westwood@emily-westwood	Running	Chrome 124	res · DE	DE	14/20	61%	96	2m
Jordan Reyes@jordan-reyes	Running	Chrome 124	res · US	US	9/20	44%	88	5m
Anya Müller@anya-mueller	Running issue	Chrome 123	res · DE	DE	6/20	38%	72	18m
Daniel Kim@dkim-revenue	Login issue	Chrome 124	res · GB	GB	0/20	-	41	3h
Sofia Bianchi@sofia-b	Running	Chrome 124	res · IT	IT	18/20	57%	94	1m
Marcus Hale@marcus-hale	Running	Chrome 124	res · US	US	11/20	49%	90	8m

Every account: its own browser, proxy, warm-up state and daily budget

Why accounts survive here

Limits before actions

Warm-up curves and health-aware daily caps are checked server-side before each send. No client can outrun them.

Isolated by design

One anti-detect cloud browser and one dedicated residential proxy per account. No shared fingerprints, no extension in your everyday Chrome.

Everything logged

Every connect, message and sync lands in the activity log, so you can see exactly what each account did and when.

Pacing, not flat caps

Limits that follow the account, not a setting.

Flat "50 invites a day" settings are how accounts die: a fresh profile and a five-year-old one cannot share a ceiling. Here every account gets its own budget:

New accounts ramp up over weeks on a warm-up curve, not from day one at full speed
Budgets adapt to account health and back off when LinkedIn pushes back
Invites, messages, InMails and profile actions each pace separately, per account

The result is boring in the best way: GTM API reports 20,000+ accounts in production at under a 1% ban rate.

Account healthcohort percentile · last 30d

Acceptance rate 72% p85

Reply rate 24% p78

Search usage 58% p64

Warning flags low p92

/api/linkedin-account-snapshots/search

Health drives the budget, measured against the cohort

One integration, the whole fleet

Ten seats or a thousand, same three calls.

The API is account-aware, so scaling out is a loop, not a rewrite:

Route each send through the right account; the platform paces every seat on its own budget
Webhooks push replies and accepts back per account, no polling
Connect accounts through hosted auth; sessions are kept alive and recovered automatically

# the outreach loop, per account, over REST
POST /api/linkedin-scraping/search-people-by-params   # build the list
POST /api/linkedin-enrichment/person-full-profile     # qualify first
POST /api/linkedin-messages/send                      # send from the right seat

# the same actions as typed MCP tools for agents
send_linkedin_connection_request · send_linkedin_message

The same typed contract for MCP and REST

The safety record

20,000+

accounts run in production

<1%

ban rate

100%

actions logged

local agents or extensions

Production numbers self-reported by GTM API; safety record verified by MirrorProfiles.

Scale LinkedIn without burning seats

Connect an account, let it warm up, and grow the fleet from there. Start on the free plan, no card.

Start free

Infrastructure

Messaging

Scraping

Enrichment data