Consensys scales secure Web3 support with Intercom Fin AI Agent, resolving over 70% of conversations
Consensys served millions of pseudonymous global customers managing tokens, wallets, and financial access at high stakes, while slow support created exploitable windows for scammers. Their legacy two-vendor stack for ticketing and live chat was too slow, expensive, and rigid to iterate fast enough to keep users safe.
Consensys's legacy stack relied on two established vendors — one for ticketing, one for live chat — with heavy dependence on vendor-led bots and professional services that made every configuration change an external project, leaving the team unable to own or rapidly adapt their automation stack.
Within 8 weeks Fin was resolving nearly 70% of support conversations with matching CSAT.
Today Fin handles approximately 20,000 resolutions per month with 90% involvement in conversations and a resolution rate over 70%, while real-time translation serves users across nearly 200 countries, enabling a true AI-first support organization.
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Frequently asked questions
What did this team achieve with this AI workflow?
Within 8 weeks Fin was resolving nearly 70% of support conversations with matching CSAT.
What tools did this team use?
Fin, Intercom, Messenger.
What results were reported?
Resolution rate within 8 weeks: nearly 70%; Monthly resolutions: ~20,000; Resolution rate vs competitors: 20%; CSAT vs competitors: 15% (source-reported, not independently verified).
What failed first in this deployment?
Consensys's legacy stack relied on two established vendors — one for ticketing, one for live chat — with heavy dependence on vendor-led bots and professional services that made every configuration change an external p…
How is this customer support AI workflow structured?
Customer contacts support → Fin AI resolves conversation → Real-time translation → Complex queries routed to humans → Fast resolution closes scammer window.