Build an Automated Client Intake and Onboarding System

Most service businesses use a combination of a web form tool like Typeform and a CRM like HubSpot. When a client submits a form or emails a signed PDF, an automation can create a new contact. The process breaks down because the automation can't read the content inside the attached document.

Consider a 15-person marketing agency. A new client emails a completed 12-page onboarding questionnaire as a PDF. The project manager must open the PDF, find the client's business address, billing contact, and project goals, then copy-paste these into five different fields in their CRM. This takes 15 minutes per client and is prone to typos. If the billing contact is missing, it creates a delay of 24-48 hours while the PM follows up.

The structural problem is that these tools are not content-aware. A CRM sees a file attachment, not the information inside the file. It can trigger a workflow when a file is added, but it cannot parse the text to check if the "Billing Contact Email" field is present and correctly formatted. This architectural gap means a human must always act as the bridge between unstructured documents and structured CRM data.

This manual bridge creates a slow, error-prone start to every new client relationship. For every 100 new clients, that's over 25 hours of administrative work. A single typo in a billing address can delay the first invoice, directly impacting cash flow and creating a poor first impression.

The engagement would begin with an audit of your current client intake process. Syntora maps every step, from the moment a document arrives to its final destination in your CRM. We would review 3-5 of your past onboarding documents (questionnaires, MSAs, SOWs) to identify the exact data fields that need extraction. This defines the data schema for the entire system.

The technical approach uses an AWS Lambda function that triggers when a new document is received. The function calls the Claude API, providing it with the document and a structured schema for the data to be extracted. Syntora uses Claude's tool_use feature for this, as it reliably forces the AI's output into a predictable JSON object. This parsed data is then validated with Pydantic before being sent to your CRM's API. We have used this document processing pattern for complex financial analysis; it applies directly to client onboarding documents.

The delivered system is a fully automated pipeline that you own completely. You receive the complete Python source code in your GitHub repository, deployed on your AWS account, typically costing under $15/month to run. A runbook explains how to monitor the system and update the extraction logic if your forms change. The system would handle over 98% of incoming documents with zero manual intervention.