Automate Client Data Entry and Communication for Your Firm

Most small consulting firms run on HubSpot for CRM and QuickBooks for accounting. While these tools have basic API access, they expect structured data. They cannot read a PDF of a signed Statement of Work (SOW) emailed by a new client and understand what to do with it. This creates a painful, manual gap between a closed deal and a kicked-off project.

In practice, this means a partner forwards the signed SOW to an administrator. That person spends 30 minutes manually creating a new customer in QuickBooks, creating a new deal or company in HubSpot, cross-referencing to avoid duplicates, and then drafting a generic welcome email. Every manual keystroke is a chance to misspell a name, enter the wrong project value, or forget a crucial detail mentioned in the SOW, leading to invoicing errors and a poor first impression.

Some firms try to patch this with pre-built integration tools. However, these tools fail because they are built for simple, one-to-one field mapping, like connecting a web form to a CRM. They cannot perform conditional logic based on the content of a document. For example, an integration cannot read an SOW, identify the project type as a 'Strategy Retainer,' and then trigger a specific onboarding sequence with the correct project template and welcome email variant. The integration tool sees a file, not the business context within it.

The structural problem is that off-the-shelf software is designed for structured, predictable inputs. The reality of professional services is unstructured data: emails, PDFs, and Word documents that contain the most critical client information. Without custom engineering to interpret this data, firms are stuck with expensive, error-prone manual processes that steal time from billable work.

The engagement would begin with a discovery process to map your exact client onboarding workflow. Syntora would audit your standard SOWs, contracts, and client emails to identify all the key data points that need to be extracted. We would then map these data points to the specific fields in your HubSpot and QuickBooks accounts. This produces a clear data flow diagram that you approve before any code is written.

The technical approach would be a dedicated FastAPI service that exposes a unique email address for your firm. When you forward a signed SOW to this address, the service triggers an AWS Lambda function. This function uses the Claude API to parse the document, extracting entities like client name, address, project start date, and billing terms with over 99% accuracy. Pydantic data models validate the extracted information against your required formats before making any API calls to your other systems.

The delivered system fully automates the setup. The extracted data populates new records in HubSpot and QuickBooks via their respective APIs. The system then uses the same data to draft a personalized welcome email, ready for a final human review. The entire process, from receiving the email to having records created and a draft ready, would take under 60 seconds. You receive the full Python source code and a runbook for maintenance.