The shape
Three loops, running on top of one model layer.
Content compounds on the client's subdomain. Paid ads prune themselves nightly. Outbound speaks in the client's voice. All three feed the same attribution graph.
Content
Articles that compound
Marcus, Jordan, Priya. Friday batch, weekend review, Monday publish.
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Ads
Self-pruning campaigns
Nightly optimization, 7-day measurement, auto-rollback at -10% or -2σ.
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Outbound
LinkedIn + email, voiced
Voice model trained on day 1, fidelity within 60 days.
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The model layer
One model under every loop.
The same model layer, Elysia, writes the content, the ads, and the outbound. Train it once on the client's voice and every channel sounds like them.
Voiced
Trained on the client
It learns the client's voice from the first day and gets sharper with every edit your team approves.
Shared
One brain, every channel
Content, paid, and outbound draw on the same model, so the message stays consistent wherever it shows up.
Reviewed
Nothing ships unseen
It drafts and proposes. Your team reviews and approves. The platform only publishes what you sign off on.
The agents
Eight specialists. One job each.
Marcus
Drafts long-form articles
Priya
Edits to client voice
Jordan
Reactions, opinions, takes
Samira
SEO meta + structure
Felix
Paid-ad copy + variants
Virgil
Outbound first-touch + reply triage
Echo
Voice-model training + fidelity scoring
Pulse
Attribution + reporting
The closed loop
Click to revenue, traced.
In
Every touch captured
Visits, leads, and replies are tied back to the work that created them.
Through
One attribution graph
Content, ads, and outbound feed a single view, so credit is measured, not guessed.
Out
Revenue you can point to
The report shows what moved the number, not just what was published.
Know the field
See where every client stands against their competitors.
See the platform live