Affinity built a moat around relationship intelligence. Its LinkedIn sync maps warm introduction chains, mutual connections, and the exact moment you met someone. That depth is exactly why migrating to Orin feels like leaving money on the table. The honest truth: you can't port Affinity's relationship graph directly into Orin . LinkedIn APIs have tightened. But Orin rebuilds relationship depth faster than you'd expect—through email threading, calendar history, and deal context. The migration isn't a lift-and-shift; it's a rebuild with better foundations. This playbook maps what transfers cleanly, what gets orphaned, and a realistic 60-day rebuild so you don't lose deal momentum during the move. What transfers without friction Start with the safe export. Affinity's core data model is solid; it's the relational metadata that doesn't travel. Contact records (name, email, phone, company): Export as CSV, import to Orin. No loss. Match on email domain to catch duplicates. Company data (industry, size, location, LinkedIn URL): Transfers cleanly. Orin's CRM contact model normalizes this automatically. Deal records (title, amount, stage, owner, close date): CSV export, map stages to Orin's pipeline. Probability and forecast math differ slightly—recalibrate on import. Notes and custom fields: Export as text; they land in Orin's note field. Formatting flattens, but the content survives. Deal history (created date, moved date, stage transitions): Timestamps preserve. Orin logs all changes; you won't lose audit trails. Pro tip: Export from Affinity to a Google Sheet first. Audit for duplicates, format mismatches, and orphaned deals before importing to Orin. One clean pass prevents silent data debt. Where relationship depth gets orphaned Affinity's secret sauce—and Orin's initial gap—is the relationship metadata that doesn't fit in a contact record. LinkedIn warm introduction chains: "Met at Disrupt 2021, introduced by Sarah Chen, who works with Stripe." Affinity maps this as navigable graph edges. Orin doesn't auto-ingest LinkedIn APIs. You'll lose the warm intro genealogy unless you manually rebuild it in notes. Mutual connection depth: "You have 47 mutual connections, strongest with Chen, Patel, and Rodriguez." Affinity scores these. Orin has no equivalent. You're starting from zero on relationship strength. Interaction recency scoring: Affinity shows "last touched 23 days ago" with a color-coded warmth metric. Orin doesn't have this built-in, though Orin's AI can infer it from email and calendar history. Custom relationship types (advisor, investor, champion, blocker): Affinity lets you tag these granularly. Orin supports custom fields; they migrate as text, not as first-class relationship dimensions. You lose the semantic weight. The key insight: Affinity's graph is a view . It doesn't live in the database; it's computed from LinkedIn APIs in real-time. Orin builds relationship depth differently—through your actual communication history (email, calls, meetings). That's slower to index initially but more accurate over time. Why email threading and calendar beat LinkedIn syncs This is the pivot. Affinity's strength was breadth (LinkedIn's network). Orin's strength is depth (your actual communication with someone). When you import your Affinity contacts and email history into Orin, here's what Orin reconstructs automatically: Email threading: Orin groups all emails with a contact (and their replies) chronologically. You see the full conversation arc—proposal, objection, deal stage shift—without manual scrolling. Affinity doesn't thread email in the same way. Calendar history: Orin syncs your calendar. Every meeting with a contact is logged and linked to the contact record. Affinity captures this but doesn't weight it as heavily in relationship scoring. Deal engagement velocity: Orin timestamps every email, call log, and meeting tied to a deal. You can see whether engagement is climbing or cooling in real-time. That signal is worth more than "we have 12 mutual connections." Cross-functional visibility: When a contact emails your support team, account manager, or CEO, Orin surfaces all of it on the contact record. Affinity doesn't have this multi-team context. So while you lose Affinity's LinkedIn graph, you gain a relationship view that's based on actual behavior , not network proximity. After 90 days, most teams say Orin's relationship picture is more actionable. The 60-day rebuild plan Don't try to reconstruct warm intro chains manually. Instead, systematically rebuild relationship scoring using fresh data. Days 1–14: Export, audit, and import Export all contacts, companies, and deals from Affinity as CSV. Deduplicate in a spreadsheet (search for variant name spellings, domain mismatches). Import to Orin. Map deal stages; set owners; validate email deliverability on 5% of records. Preserve Affinity's custom fields as plain-text notes if Orin field types don't match. (Don't force-fit; data integrity first.) Do not impo