11,000 historical attendances and 117 events backfilled into Attio without disrupting the live event-management platform

The situation

The client runs an UHNW member network — a few hundred members, dozens of events per year, deep relationships built over years of curated dinners and gatherings. The operational stack was working fine for events but failing on every other dimension:

• Event platform was the source of truth for events — but every member relationship insight (who attended what, who invited whom, who skipped the last three) was trapped inside it with no clean export.
• 5+ years of historical attendance was locked behind an event-platform UI not built for analytical queries.
• New members were captured via Typeform with no automation between intake and the operational systems.
• Invoicing and member admin lived in a separate stack that didn’t know about engagement.

The brief: bring it all into Attio without rebuilding the event platform itself, and keep them perfectly in sync going forward.

What we built

Three live workflows plus a one-time historical backfill, all running on a hybrid Attio + n8n architecture.

WF1  Typeform → Attio member intake          (native Attio)
WF2  Event RSVP → Attio attendance record    (native Attio)
WF3  Event check-in → Attio + cross-ref      (hybrid: n8n + Attio)

backfill: 11,000 attendances + 117 events    (direct Python, sequential)

Workflow 1 — New member onboarding (native Attio)

Typeform submission → member record created in Attio → enrichment → routed to the right relationship owner. Built natively in Attio’s automation engine because the logic was simple and didn’t need external infrastructure.

Workflow 2 — Event RSVP sync (native Attio)

When a member RSVPs to an event in the event platform, the Attio attendance record is created or updated. Native again — Attio’s webhook + automation can handle this without n8n in the loop.

Workflow 3 — Live attendance tracking (hybrid Attio + n8n)

Real-time attendance check-ins from the event platform → n8n webhook → resolves attendee + event records via the platform’s API → writes the attendance record back to Attio with the right relationship attributes. The n8n layer was needed here because the event platform’s webhook payload required cross-referencing multiple endpoints to resolve full member context.

event platform  ─webhook→  n8n
                            ├─ resolve attendee → fetch member context
                            ├─ resolve event    → fetch event metadata
                            └─ write Attio attendance record
                                   ├─ link to Person (member)
                                   └─ link to Event (object)

Historical backfill — 11,000 attendances, 117 events

A direct Python script (not an n8n workflow) sequentially pulled every 2025 + 2026 event from the platform’s API, every attendance record, and every member context, then wrote them into Attio with full relationship attributes preserved. Direct Python beat n8n here because n8n’s parallel execution races against Attio’s rate limits at this scale — sequential beats parallel for >500-record backfills.

Outcome

• All 3 workflows live and stable. Every new event syncs the moment it’s created in the event platform.
• 11,000+ historical attendances + 117 events imported with full member relationship attributes preserved.
• Member operations now answer the question that mattered: “who has attended what, when, with whom, and how engaged are they overall?” — in seconds, in the same workspace where outreach gets done.

Why this matters for member networks

Member networks live or die on relationship quality. The historical pattern of “who attended what, with whom, and how often” is the most valuable data the organization owns — and in most network operations, it’s locked inside an event-management tool that wasn’t built to surface it. The right answer isn’t to rip out the event platform (it works for events). The right answer is to make Attio the relationship layer that sits on top, fed in real time from every event the platform handles. We built exactly that — and the historical backfill made it useful from day one instead of starting from a blank workspace.