Your moments feed your own marketing.
Every revenue moment Inception Agents records — wall hit, trial started, upgrade accepted — reaches your email platform, CRM, or warehouse as a signed event. It's intent your funnel has never had, in the channels you already run.
The moment outlives the thread.
A trial nears its end inside an agent session; the thread closes — and a signed event reaches your email platform, carrying context that was recorded at the blocked tool call. Wall hit, trial started, upgrade accepted, value delivered — to any endpoint you name.
- Signed HTTP events with a stable core — enrichment grows, your integration doesn’t break.
- Pseudonymous by construction: subject references you resolve against your own users. Never PII from us.
- Test deliveries, a delivery log, and signature verification before anything goes live.
Intent your analytics can't see.
Which moments convert, which get abandoned, what each is worth — per agent environment, per lifecycle stage, free through paid. It exists only at the blocked tool call, so it's pre-checkout intent Stripe never sees and no analytics vendor can reconstruct.
- Your single-tenant analytics are yours — in your dashboard, nobody else’s.
- Cross-tenant learning is privacy-gated aggregates only. Never your raw data.
- Every moment you record sharpens your own playbook — your history stays yours.
Attribution with nothing to argue about.
An authenticated MCP session maps to a pseudonymous per-user subject, which maps to a Stripe customer, which maps to a completed checkout. Every link in that chain is deterministic. No cookies, no probabilistic modeling, no attribution debate — and for a brand-new trial or free converter, checkout mints the Stripe customer inline. Still deterministic, still cookie-free.
- subject_ref is vendor-hashed and PII-forbidden by contract.
- The checkout outcome is stitched back through Stripe metadata — not inferred.
- Determinism is what makes outcome-based pricing credible at all.
Coarse intents, fine facts, and a decision engine in between.
Cross-tenant learning only aggregates if the vocabulary is shared. Canonical buying intents and an eight-class commercial-trigger taxonomy stay deliberately coarse — that's what makes patterns comparable across vendors. Fine-grained variety lives in namespaced facts. Above both, a Thompson-sampling engine learns which offer framing works — always inside guardrails you set.
- Intents coarse, facts fine — the discipline that keeps network learning real.
- The engine optimizes framing within your messaging constraints, never around them.
- Every experiment is grounded in a recorded moment, like everything else here.
This is where you feed your own marketing.
Every moment makes the next one convert better.
Start capturing yours today — moments appear in your dashboard the day you install.