Automate Proposal and SOW Drafting for Your Agency
Yes, AI agents can automatically draft project proposals for a marketing agency from discovery call transcripts. The system extracts scope, pricing, and client details, then generates a structured document for review.
Key Takeaways
- AI agents can automatically draft project proposals for marketing agencies by extracting scope from call transcripts.
- The system generates a structured JSON object from the conversation, then produces a final HTML or PDF document.
- This automation reduces post-call document drafting from 3-4 hours to under 30 minutes.
Syntora builds AI automation for professional services firms to draft proposals and SOWs directly from call transcripts. Syntora's system uses the Claude API to extract scope and pricing from Gong recordings, reducing post-production time from 4 hours to 30 minutes. The automation pipeline connects to Salesforce and generates print-ready HTML documents with dynamic legal clauses.
Syntora built its own proposal generation pipeline using the Claude API and Fireflies transcripts to solve this exact problem internally. For a marketing agency, the complexity depends on the structure of your proposals and where client data is stored, such as in Salesforce or HubSpot.
The Problem
Why Do Marketing Agencies Waste Hours on Manual Proposal Writing?
Most marketing agencies use tools like PandaDoc or Proposify. These are powerful template libraries that speed up document formatting but do nothing to help with content extraction. An account executive still manually listens to a 60-minute Gong recording, pulls out the client's pain points, lists the deliverables, and types them into the template. The core bottleneck, turning a conversation into structured scope, remains untouched.
Consider an account manager at a 20-person digital PR agency after a discovery call. The recording is in Gong, client notes are in Salesforce, and the Master Services Agreement (MSA) is a separate PDF. The manager spends the next three hours re-listening to the call, pulling out scope items, cross-referencing Salesforce notes, and ensuring nothing in the new Statement of Work contradicts the MSA's payment terms. They inevitably miss a detail, like the client asking for weekly, not monthly, reporting. The SOW goes out, gets signed, and a month later a client dispute begins.
The structural problem is that template tools are architected for document assembly, not data extraction. They operate on static variables like {{client_name}} that you fill in. They have no understanding of the unstructured conversation that precedes the document. Connecting a CRM helps with contact info, but the core task of defining project scope from a dialogue is an AI language task, not a document formatting task.
Our Approach
How Syntora Builds an Automated Proposal and SOW Pipeline
We start by analyzing your existing proposals and SOWs. We map out every variable field, conditional clause, and data source you use. The goal is to create a definitive JSON schema that represents any proposal your agency might write, from a simple content retainer to a complex multi-channel campaign. This schema becomes the blueprint for the entire system.
We built a pipeline that uses the Claude API to process call transcripts from services like Gong or Fireflies. The AI agent extracts key entities like pain points, scope items, and pricing, then populates the predefined JSON schema. A FastAPI service manages this process and validates the output. For SOWs, a separate JSON configuration file drives an HTML generator, dynamically inserting pre-approved guarantee clauses or case study permissions based on deal parameters from Salesforce.
The delivered system connects directly to your call recording software and CRM. After a call, a draft proposal or SOW appears in a review queue within 5 minutes. Your team reviews the AI-generated draft, makes any necessary edits, and clicks to publish. This pipeline reduces the 3-4 hours of manual post-production work to a 30-minute review cycle, removing a major bottleneck in the sales process.
| Manual Proposal Process | Syntora's Automated Pipeline |
|---|---|
| 3-4 hours of re-listening to recordings and typing | Under 5 minutes for an AI-generated first draft |
| Manual copy-paste from Gong, Salesforce, and MSAs | Direct API connection to call transcripts and CRM data |
| High risk of missing scope items discussed on a call | AI cross-references transcript to ensure all discussed items are included |
Why It Matters
Key Benefits
One Engineer, Direct Collaboration
The engineer on your discovery call is the same person who writes the production code. No project managers, no communication gaps, no offshore handoffs.
You Own All the Code
You receive the full Python source code in your private GitHub repository, plus a runbook for maintenance. There is no vendor lock-in.
Realistic 4-Week Build Cycle
A typical proposal automation system is scoped, built, and deployed in about 4 weeks. The timeline depends on the number of document templates and data sources.
Predictable Post-Launch Support
After the system is live, Syntora offers an optional flat-rate monthly support plan covering monitoring, API updates, and prompt tuning.
Built for Agency Workflows
Syntora understands the professional services sales cycle. The system is designed to handle MSA contradictions, dynamic guarantee clauses, and other agency-specific complexities.
How We Deliver
The Process
Discovery & Scoping
A 30-minute call to understand your current proposal process and tools. Syntora provides a detailed scope document within 48 hours outlining the build, timeline, and a fixed price.
Architecture & Data Access
You approve the technical architecture and provide read-only access to your CRM (e.g., Salesforce) and call recorder (e.g., Gong). No build work begins without your sign-off.
Iterative Build & Review
You get weekly updates and see the first generated documents within two weeks. Your feedback on the output quality directly informs the prompt engineering and validation logic.
Handoff & Training
You receive the complete source code, a deployment runbook, and a training session for your team. Syntora monitors the system for 4 weeks post-launch to ensure stability.
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The Syntora Advantage
Not all AI partners are built the same.
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Assessment phase is often skipped or abbreviated
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We assess your business before we build anything
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Typically built on shared, third-party platforms
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Fully private systems. Your data never leaves your environment
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May require new software purchases or migrations
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Zero disruption to your existing tools and workflows
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Training and ongoing support are usually extra
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Full training included. Your team hits the ground running from day one
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Code and data often stay on the vendor's platform
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You own everything we build. The systems, the data, all of it. No lock-in
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