ProspectHalo

ProspectHalo runs an autonomous B2B prospecting cycle: you describe your ideal customer once in plain English, and the agent finds matching contacts daily, verifies their current role on LinkedIn, validates their email before any send, scores each lead against your ICP, and queues them for outreach. Sequences run across LinkedIn and email from your own connected accounts — Gmail, Outlook, Google Workspace, LinkedIn — with daily sending caps and automatic account ramp-up built in so no single account absorbs a spike that draws a ban.

The intent-scoring layer is the differentiator that separates this from a simple sequencer. The agent reads signals — whether a prospect is actively hiring SDRs, whether they already use a named competitor, how active they are on LinkedIn — and surfaces the hottest leads first. That means the agent is not just sending volume; it is prioritizing the contacts most likely to be mid-evaluation right now.

For founders running their own outbound or small sales teams without a dedicated SDR function, the pitch is real: the manual loop of list-building, email verification, personalized copywriting, follow-up tracking, and reply triage is genuinely collapsed into one surface. The reply inbox auto-sorts by intent — interested, question, not now — and autopilot mode lets the agent respond to warm replies and book the meeting directly. You can review every message before it sends, review only the first, or let it run entirely unsupervised.

The system runs exclusively in the cloud with no self-hosted option and no public API documented on the vendor page. Teams that need outbound data piped into a CRM with custom field logic, or that require sequence branching based on specific reply content parsed by their own models, will find ProspectHalo’s architecture too closed. It is built to own the whole loop — which is its strength for simple outbound and its hard boundary for teams that need outbound as one node in a larger revenue stack.