Custom AI for Contract Generation and e-Signatures

Many service businesses start with tools like PandaDoc or DocuSign CLM. These platforms work well for simple variable replacement, like inserting a client's name and address. Their limitations appear when your SOWs require complex conditional logic. For example, if a client selects 'Service A', you must include paragraph X and add a specific setup fee, but if they also select 'Service B', paragraph X must be replaced with Z. This logic often breaks template engines, forcing your team back into manual document editing.

CRM-native tools like the HubSpot Quote Builder are designed for product sales, not services. They generate line-item tables that look more like an invoice than a professional Statement of Work. They cannot accommodate the detailed scope descriptions, deliverable timelines, and legal clauses that a service agreement requires. The result is a broken workflow where a team generates a basic quote, then copies the information into a Google Doc to manually write the actual SOW, which takes another 30 minutes and risks data entry mistakes.

The core issue is architectural. Off-the-shelf document tools are built for static templates with simple fill-in-the-blank fields. They are not designed for generative document assembly, where business logic fundamentally changes the structure of the document itself. When your process depends on complex rules that add, remove, or modify entire sections of a contract, you need a system built around logic, not just a template.

The first step is a discovery process to audit your existing contracts and SOWs. Syntora maps every variable field, conditional clause, and data source you currently use. This audit produces a structured data model of your documents, defining exactly what information is needed to generate any contract variation automatically. You receive this schema for review, ensuring the system will capture the business logic your team now handles manually.

We would build the system around a FastAPI service running on AWS Lambda for efficiency and low cost. When triggered from your CRM, the service pulls deal data via API. The Claude API then interprets this data to handle complex tasks, like summarizing project notes into a scope description or selecting the correct legal clauses based on service type. We've built similar document processing pipelines for financial documents, and the same pattern of extracting structured data applies directly here. The system generates a finalized PDF and sends it to an e-signature API like HelloSign.

The delivered system integrates directly into your team's existing workflow. A user clicks a 'Generate SOW' button on a deal record in your CRM. Within 60 seconds, a draft is ready for review. After approval, another click sends the document for e-signature. All status updates, such as 'viewed' or 'signed', are automatically written back to a custom field on the CRM deal record. You receive the complete Python source code and a runbook for maintenance.