Five agents, online
Not one "AI SDR." Five specialized agents over one CRM: a shared vector index, dedup-keyed catalyst signals, your TOV Database (tone-of-voice), a usage meter you can read. Every claim cites a signal, a record, or a doc. Scroll: each one runs right here.
Drafts that sound like you wrote them.
Origin composes outbound as a strict JSON contract: {subject, body, hook, tone}. Sixty to 110 words, one hook, one call to action. Voice is not a dropdown: it is retrieved from your TOV Database profile, the writing samples, posts, and style notes you load once on your profile. Every draft lands in your approve / edit / reject queue, Origin writes, you ship. It reads the thread history and the record before it opens its mouth. Either way, per-prospect memory means it never repeats a hook.
A pre-call brief before the call starts.
One call, five sections: snapshot, recent moves, decision-maker map, talking points, risks. Every line is tagged [signal], [crm], or [general] so you know exactly where a claim came from. Thin data stays thin; the agent will not pad a two-signal company into a ten-line story, and it never invents a name that is not in your CRM.
Virtual BDRs with fixed personas.
You build each Legion member once, strengths-style: territory, deal band, voice, and two strengths, compiled into a system prompt and persisted. Then you point it at accounts and it runs. Every run lands in your queue, approve, edit, reject. Output is attributed to the member that wrote it, so you can see which persona actually earns its seat. The console below builds one live: spawn your own.
Chat over your org's knowledge.
Every uploaded document is chunked into an org-scoped index, brain_<org_id>, and answers cite document_id plus version_id. That makes citation logs double as coverage analytics: you can see which docs answer real questions and which are dead weight. Tier gating happens at the wrapper and again at the route, so a downgraded org fails closed.
Watches the whole lifecycle.
Customer Success does not wait to be asked. Four triggers: new prospect, stage change, fresh signal, seven days of silence. Each one fires a time-bound recommendation into agent_recommendations. Every rec carries the reasoning and confidence that produced it, and Enterprise runs pull your Brain docs in, so recommendations cite your SOP, not a generic playbook.
Agents are only as good as the data underneath.
This is the part nobody demos. An agent pointed at raw inboxes and spreadsheets burns most of its tokens guessing at structure. Ours start from a CRM: clean records, deduped signals, scoped indexes. Same tasks, a fraction of the spend.
The next three are on the bench.
Scoped, storyboarded, and in the build. What's below is the shape we're shipping to, not a running agent. Subscribers hear first; beta invites go out in signup order.
Run them on your pipeline.
The demos above are scripted. The real ones read your CRM, your signals, and the writing samples you loaded. The CRM is free; the AI agents run on credits.