HeyReach

Automation — sequenced LinkedIn outreach at scale

The core object in HeyReach is the campaign: a sequence of steps — visit profile, send connection request, wait, send message, wait, send a follow-up — built once and run against a list of leads pulled from a LinkedIn Sales Navigator search, a saved list, or a CSV import. Multiple LinkedIn accounts can run the same or different campaigns in parallel, which is the main way HeyReach adds throughput beyond what one account could safely send.

Reply detection is the one piece of real logic in the sequence engine — when a lead responds, HeyReach stops sending further scripted steps to that lead automatically, so people don't keep receiving a canned follow-up after they've already answered. Beyond that, sequences are linear or lightly branched (for example, a different message if a connection request wasn't accepted), not a general-purpose workflow builder.

Account safety is handled through pacing controls: a warm-up period that ramps daily connection and message limits gradually on new or reactivated accounts, and per-account daily caps you set to stay under LinkedIn's informal action limits. This matters because the platform runs cloud-side rather than as a browser extension, which is part of why accounts used this way tend to carry lower ban risk than extension-based tools — but it's still not risk-free, and caps still need to be set conservatively.

For agencies, workspaces separate campaigns, leads, and reporting per client, so one team can run outreach for multiple accounts without data bleeding between them.

Outside LinkedIn itself, HeyReach connects out through its API, webhooks, and native or Zapier and Make integrations — syncing new leads into a CRM, triggering a Slack alert on a reply, or pulling enriched contact data in from tools like Clay before a campaign starts.

What we actually build with you is the sequence design (step count, wait times, message variants), the per-account sending limits, the lead sourcing method, and the integration wiring to your CRM or notification tools — the parts that determine whether a campaign performs and stays within safe sending behavior.

HeyReach use cases for Automation

HeyReach helps teams execute repetitive tasks at scale with confidence. The use cases below reflect practical, implementation-ready opportunities that leverage HeyReach capabilities and your data.

• Automated lead routing based on intent signals and account attributes, with real-time contention handling.
• Incident triage automation that categorizes issues, seeds remediation workflows, and escalates only when necessary, reducing MTTR.
• Data enrichment pipelines that harmonize contact data from multiple sources, validated by HeyReach governance rules.
• Report generation and distribution automation that assembles dashboards, schedules delivery, and flags anomalies for review.
• Marketing operations automations that synchronize campaigns, audiences, and budget pacing across platforms.
• Order processing and fulfillment automation that validates inputs, triggers downstream actions, and records outcomes for compliance.
• Customer onboarding tasks automated from welcome emails to system provisioning, guided by policy guards.
• Security-informed automation that applies role-based access controls and audit trails to routine tasks.
• HR admin automation, including payroll data checks, benefits enrollment, and compliance reporting.
• Quality assurance triggers that automatically validate data and flag deviations for human review.

As you scale, HeyReach supports expanding automation to new domains by building on a proven framework, ensuring consistency and reuse. TheHeyReach team collaborates with you to prioritize automation backlogs and maintain alignment with corporate objectives.

Closing note: HeyReach helps you turn automation into a capability rather than a project, so your teams can maintain momentum while governance keeps risk in check.

AI — the honest answer is "not really"

HeyReach does not run a generative AI model, and it doesn't market itself as an AI product. What it actually does is orchestrate LinkedIn (and, on relevant plans, email) outreach sequences across multiple sender accounts — connection requests, follow-up messages, profile visits, and replies — using conditional logic rather than machine learning. If you came here expecting AI-written copy or predictive lead scoring, that's not what's in the product.

Personalization runs on merge fields — first name, company, job title, mutual connections pulled from a lead list or LinkedIn search — not generated language. Writing the actual message copy is still your job or your team's, same as it would be with any manual outreach; HeyReach's contribution is sending it at scale, in sequence, and stopping automatically when someone replies.

Where intelligence does show up is in the sending logic: reply detection that halts a sequence the moment a lead responds, account warm-up pacing that ramps daily action limits gradually instead of triggering LinkedIn's abuse detection on day one, and rotation across multiple sender accounts so volume doesn't concentrate on a single profile.

If AI-generated messaging matters to your outreach strategy, that has to come from somewhere else — a separate AI writing tool feeding copy into HeyReach via CSV import, or a webhook or API connection to your own generation pipeline. HeyReach's API and webhook support make that pairing possible; it just isn't built in.

We're direct about this distinction upfront because it changes what an engagement should focus on: not tuning an AI model, but designing sequences, safe sending limits, and lead sourcing that actually convert on LinkedIn without tripping platform restrictions.

What we help you build instead is the sequence logic and safety limits that make automated outreach sustainable: message variation to avoid spam patterns, sensible daily caps per account, and a review process for the copy that HeyReach will be sending on your behalf at volume.

HeyReach AI use cases

These scenarios illustrate concrete, production-ready AI workstreams tailored to the HeyReach platform and your data environment.

• Forecasting demand with explainable AI that reveals drivers and confidence intervals.
• Lead scoring augmented by contextual signals and continuous calibration by HeyReach teams.
• Customer support routing enhanced by intent detection and escalation rules.
• Personalized content recommendations that respect privacy and consent preferences.
• Anomaly detection in financial or operational data with automated alerting and review prompts.
• Natural language processing for summarization and contract review with human verification steps.
• Churn propensity models that inform proactive retention campaigns managed by HeyReach governance.
• Supply chain risk scoring that combines external signals with internal benchmarks.
• Credit risk assessment supported by explainable models and auditable decision trails.
• Pricing optimization suggestions surfaced through interpretable analytics and scenario testing.

HeyReach positions AI as a decision-support layer that accelerates insight while maintaining control, with governance baked into every model and workflow.