create-proposal

You can generate a follow-up email from a transcript by using a Skill that parses the sales call content, extracts key solution summaries, and formats the information into a ready-to-send HTML email to keep the sales process moving.

Yes, proposal generation requires structured JSON assembly and template token mapping to accurately populate the PandaDoc document with expanded content covering problems, benefits, pricing, and metadata extracted from the input.

You can align the proposal with a client's brand voice by applying optional client research, which reviews the client website or email domain to capture current context and tailor the generated proposal content accordingly.

Automating document creation and validation with retry handling requires structured client details or a transcript input, along with configured dependencies like python-dotenv and requests to manage API interactions and validate the assembled JSON output.

The best way to convert discovery notes into a client-ready proposal package is to input the raw notes or transcript, allowing the system to expand the content into structured proposal sections and format a matching follow-up email without manual drafting.

You should avoid automated proposal generation when your sales team requires custom document structures outside the predefined template token mapping, or when the input discovery notes lack sufficient detail for accurate JSON assembly and validation.