Intake
Client intake calls to structured requirements
Thesis
Client intake calls are unstructured and notes get lost. Transcription APIs are mature enough to extract structured requirements automatically, saving 2+ hours per client.
The Problem
Discovery calls are where projects go wrong before they start: Someone takes notes (maybe). Requirements get scattered across emails, docs, and memory. By the time you write the SOW, you've forgotten half of what was discussed. Gaps don't surface until the project is underway. The irony? The client told you everything you needed. You just didn't capture it in a usable way.
Implementation Approaches
Meeting Bot + Extraction (Recommended)
Bot joins calls, transcribes, and extracts structured requirements
Implementation
- →Zoom/Meet/Teams bot joins scheduled intake calls
- →Real-time transcription via Deepgram or Assembly
- →Claude extracts: goals, requirements, constraints, timeline, budget signals
- →Flags gaps: 'Budget not discussed', 'Timeline unclear'
- →Outputs draft SOW sections ready for review
Pros
- +Captures everything, not just what someone remembers to write
- +Flywheel: learns what good intake questions look like over time
- +Connects to Guildry's scoping module directly
- +High value per call justifies premium pricing
Cons
- −Meeting integrations are complex
- −Privacy concerns, some clients won't want recording
- −Depends on call quality and clear discussion
Post-Call Upload
Upload recordings after the fact for processing
Implementation
- →Upload audio/video from any source
- →Same extraction pipeline, no live integration needed
- →Works with existing recording workflows
- →Can process historical calls to build training data
Pros
- +Fastest to build, no meeting integrations
- +Works with any recording tool or phone call
- +Lower privacy friction, user controls what gets uploaded
- +Can process backlog of past calls
Cons
- −Extra step, users might not bother
- −No real-time value during the call
- −Harder to build habit
Guided Interview Tool
AI-guided intake form that asks the right questions
Implementation
- →Send client a link before/after the call
- →AI asks clarifying questions based on project type
- →Combines with call notes for complete picture
- →Generates structured brief automatically
Pros
- +No recording needed, pure async
- +Client does some of the work
- +Can use before call to prep, or after to fill gaps
- +Reuses Brief's conversation patterns
Cons
- −Requires client participation
- −Doesn't capture the nuance of live conversation
- −May feel redundant if call happened
Validation Plan
Hypothesis to Test
Agencies will pay $29/mo to turn intake calls into structured SOW drafts automatically
Validation Phases
Manual Extraction
1 week- •Get 5 intake call recordings from agency contacts
- •Manually extract requirements using Claude
- •Generate draft SOW sections
- •Show output to agencies, gauge reaction
Upload MVP
1 week- •Build simple upload and extraction flow
- •Partner with 3 agencies for pilot
- •Process their real intake calls
- •Measure: time saved, quality of extraction
Pricing + Integration
2 weeks- •Add meeting bot integration for one platform
- •Propose pricing: $29/mo for 10 calls, $79/mo unlimited
- •Connect output to Guildry's project creation
- •Track: calls processed, conversion to paid
Kill Criteria
Stop and move on if any of these become true:
- ✕Extraction quality too inconsistent for real use
- ✕Agencies don't actually process enough calls to justify subscription
- ✕Privacy concerns kill adoption
- ✕Existing transcription tools are 'good enough'