
FontFind — Poster Font Identification & License Checker
Upload any poster — FontFind automatically identifies every font, shows license info and free alternatives. No manual letter labeling.
Over dit model
Overview
FontFind is an automated font identification and typography intelligence platform that converts any poster, flyer, logo, packaging asset, or photo of text into a named, license-checked type system in seconds.
The Problem
Designers, marketing agencies, print production shops, and brand managers identify typography from real-world posters and graphics daily. Existing legacy tools are broken:
- Manual Character Boxing: Incumbents force users to manually crop, box, and type in characters one by one.
- Single-Font Blindness: Real posters combine 2 to 4 fonts simultaneously (headline, subhead, body, credits); legacy tools identify only one crop at a time.
- Ghost Chasing & AI Typography: Existing tools match bespoke hand-lettering or generative AI text to commercial catalogs without warning, wasting hours searching for fonts that do not exist.
- Retroactive Licensing Exposure: Foundries increasingly issue five-figure retroactive license demands against agencies using unlicensed desktop fonts on commercial campaigns.
The Solution
FontFind automates the entire typographic workflow using a local-first computer vision and glyph contour matching engine:
- Zero Manual Labeling: Automatic text segmentation and connected-component bounding box extraction eliminate manual character labeling.
- Poster Mode: Decomposes the full typographic hierarchy in a single 2.5-second pass (Headline, Subhead, Body, Credits).
- Honest Verdicts: Distinguishes true digital fonts (<3% glyph variance) from bespoke hand-lettering or AI generation (>10% variance) using repeated-glyph variance analysis.
- Visual Proof: Renders side-by-side character comparisons and transparency overlays for sub-pixel contour verification.
- License-First Compliance: Attaches plain-language commercial permissions (OFL, Apache, Commercial) and verified open-source alternatives for commercial look-alikes.
- Local Privacy: Zero third-party cloud vision API calls; image data stays private with default 24-hour auto-purge.
Key Capabilities
- Automated Poster Mode Multi-Region Detection
- Repeated Glyph Variance & Honest Custom Lettering Detection
- Multi-Metric Glyph Distance Scoring (Hu Moments, Aspect Ratio, Stroke Weight)
- Visual Why This Match Proof & Render Verification Overlay
- Integrated License Badging & Open-Source Alternatives Mapping
- High-Throughput REST API for Automated Tooling and AI Agents
Target Personas & Use Cases
- Freelance Designers: Rapidly identify reference typography and obtain Google Fonts CSS in under a minute.
- Print Shops & Sign Makers: Digitize legacy printed collateral and flyers without manual character typing.
- Brand & Content Teams: Recreate campaign styles legally using suggested open-source alternatives.
- Developer Tools & AI Agents: Programmatically resolve screenshot typography into CSS fallback stacks.
Belangrijkste functies
Fully automatic font identification without manual letter labeling
Poster Mode identifying headline, subheadline, body, and credits simultaneously
Honest verdicts (Exact, Close, Similar, Likely custom lettering)
Repeated glyph consistency check to catch hand-lettering and AI fonts
Letter-by-letter why this match visual proof and render overlay
Plain-language usage rights, license badges, and free open-source alternatives
Local-first engine with zero third-party AI vendor cost and complete data privacy
Developer-friendly REST API for automated design pipelines and coding assistants
Use-cases
- Freelance designer uploads a client reference poster and gets exact font names, licenses, and free alternatives in under a minute
- Print shop identifies all fonts on a customer faded old flyer, region by region, without manual letter labeling
- Marketer recreates competitor campaign typography using verified free open-source alternatives
- Developer or AI agent calls the API to get exact font names and Google Fonts CSS when recreating screenshots
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