All case studies
Product

Draftigo

AI-native document drafting for professionals who write under pressure

~60%
Draft time reduction
6 categories
Document templates
In development
Status
Web + mobile
Delivery

The problem

Existing AI writing tools produce generic output because they have no context about the user, the document type, or the audience. Professionals - lawyers, consultants, engineers, founders - need drafts that match their voice, their document structure, and their field. Copy-pasting into a general-purpose chatbot and hoping for the best wastes more time than it saves, and produces output that reads like it was written by someone who has never done the job.

Our approach

Draftigo is built around three primitives: a document context layer (audience, purpose, tone, constraints set upfront per document), a structured outline mode (documents built section by section rather than in one undifferentiated prompt), and a persistent style memory (the system learns and matches the user's writing voice across sessions). Built on top of an instruction-following model with structured prompt templates per document category: business proposal, technical specification, internal brief, email thread, legal-adjacent writing, and project report. Each template enforces the structural conventions of its document type. UI is minimal by design - no distraction, no feature clutter.

Outcome

Currently in active development. Early testers report approximately 60% reduction in time from brief to first-review-ready draft. Target launch on web with a subscription model. Mobile support planned post-launch.

Deliverables

  • Core drafting engine with document context layer
  • Structured outline mode (section-by-section composition)
  • Style memory system (voice learning across sessions)
  • 6 document category templates with structural enforcement
  • Web application (React/TypeScript)
  • Subscription billing integration

Timeline

In development

Tech stack

TypeScriptReactNext.jsLLM APIsTailwindCSSPostgreSQLStripe

Tags

ProductLLMTypeScriptReactWriting AISaaSFine-tuning

Interested in this?

We take on a small number of new engagements per quarter. If this matches your problem, let's talk.

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