The Scenario
A professional services firm — accounting, legal, consulting, or advisory — receives client intake through a mix of email attachments, web forms, and PDF submissions. A team member reads each submission, extracts the relevant information, enters it into the CRM, creates a follow-up task, and sends an acknowledgment. During busy periods, submissions sit unprocessed for hours. Some details are entered inconsistently across staff members.
How It Would Work
Incoming documents — intake forms, signed contracts, questionnaires, application packages — are processed automatically. A document AI model reads the content, extracts structured data (client name, engagement type, key dates, flags, dollar thresholds), and populates the relevant fields in the CRM.
Based on the extracted data, routing rules assign the file to the right team or individual. An automated acknowledgment goes to the client. If the document is missing required information — a signature, a date, a required field — the system flags it and sends a targeted request for the gap only, not a full re-submission.
What You Would Get
- CRM populated automatically from every incoming document — no manual data entry
- Consistent field extraction regardless of which staff member handles intake
- Routing based on engagement type, client tier, or document flags — configured to your firm's rules
- Automated client acknowledgment within minutes of submission, any time of day
- A gap-detection step that catches missing information before it stalls a file
Why It Matters
Intake bottlenecks are common in professional services because intake looks simple but involves a lot of judgment calls about categorization, routing, and follow-up. Automating the structured parts of intake — data extraction, routing, acknowledgment — frees staff to focus on the parts that actually require judgment. It also removes the variability that comes from multiple people interpreting the same intake document differently.