The problem
Every new client starts with documents: identity papers, mandates, statements, signed agreements. The firm, a financial services company working in debt reconciliation and credit legal matters, requested them by hand, checked what came back, and chased what didn't. The backlog grew faster than anyone could clear it, and only 20% of potential clients ever made it through onboarding.
The choice on the table was blunt: expand the staff, or automate the process. Every applicant who gave up mid-chase was revenue walking out the door.
The system
Flairr built an AI-driven workflow that owns the whole loop. It reaches out to every new client, requests exactly the documents their case needs, and reads each file the moment it arrives: right document, complete, legible, in line with the specifications.
Valid documents are uploaded to the CRM against the client's record automatically. Anything short triggers a precise follow-up without a human touching it, and a support chatbot walks clients through the upload when they get stuck.
Guardrails
Nothing leaves the system unsupervised. Outbound requests use approved templates, every validation decision is logged and traceable, and edge cases route to a person instead of guessing. No applicant gets overlooked: if the system can't resolve a file, the team sees it the same day. Client data stays inside the firm's own environment and is never used to train public models.