Scope Your AI Proposal Automation Build

Many service businesses rely on tools like PandaDoc or DocuSign for proposals. These are effective for e-signatures and simple templates, but their logic is limited. Their content libraries store static text blocks, but they cannot dynamically calculate pricing based on project duration and a tiered discount structure. You can show or hide a section, but you cannot generate a custom payment schedule within a section based on a formula.

Consider a 20-person marketing agency preparing an SOW. The account manager pulls client data from HubSpot, checks team availability in a spreadsheet, calculates pricing based on three service tiers and a 12-month commitment discount, and then searches a folder for the right case studies. This manual process takes 90 minutes and is fragile. A single copy-paste error from an old proposal can leave the wrong client's name on page 4, or a miscalculation in the pricing spreadsheet can underbid the project by thousands.

The next step up, a tool like Salesforce CPQ, is expensive overkill. CPQ systems are built for complex product catalogs with SKUs, bundles, and hardware dependencies. They impose a rigid data model that does not fit service businesses, whose 'product' is a nuanced combination of deliverables and expertise. The structural problem is that off-the-shelf software is built for either simple templating or complex product sales, with no middle ground for custom service offerings.

The engagement starts with a process audit. Syntora maps your entire proposal workflow, identifying every data source from your CRM to your pricing spreadsheets and case study documents. We codify the business rules that live in your team's heads: how discounts are calculated, which legal clauses apply to which services, and how team allocation affects timelines. You receive a data flow diagram and a fixed-scope project plan before any code is written.

The technical core would be a FastAPI service hosted on AWS Lambda, which keeps hosting costs under $20/month. When a user requests a proposal, the service fetches client data from your CRM's API. A Python script using the `openpyxl` library reads your pricing logic directly from an Excel or Google Sheet, allowing your operations team to update rates without developer involvement. The final document is generated using `python-docx` for editable Word files or a headless browser with Playwright for pixel-perfect PDFs from an HTML template.

The delivered system is a simple web form where your team enters a client ID and a few project variables. The engine generates a complete, accurate, and consistently formatted proposal in under 10 seconds. You get the full source code in your GitHub repository, a runbook explaining how to update templates and pricing models, and a simple monitoring dashboard hosted on Vercel.