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TokenPig VS Digraph.dev

Compare TokenPig VS Digraph.dev and see what are their differences

TokenPig

Upload a document and turn it into clean, token-efficient Markdown for ChatGPT, Claude, Gemini, Cursor and RAG workflows.

Rating
0 reviews
Pricing
Freemium Free trial
Alternatives Is it good?
Digraph.dev

AI marketing platform for brands.

No screenshot yet
Rating
0 reviews
Pricing
Freemium Free trial $99 / Monthly
Alternatives Is it good?
Mind Diary
MindDiary therapy practice management software: digital intake, lead capture, client check-ins, therapist-reviewed AI notes, telehealth, and revenue follow-up. sponsored
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Markdown Converter popularity
100% vs 0%
alternatives listed
16 vs 1

Base details

Website, pricing, platforms and company facts side by side.

TokenPig
Digraph.dev
Website tokenpig.co digraph.dev
Pricing
Freemium Free trial Official pricing
Freemium Free trial $99 / Monthly Official pricing
Platforms
Web
—
Company — Startup from the United States · 1 - 9 employees
Listed in
Document Management AI Tools PDF Converter Document Converters Markdown Converter Markdown AI +4
SaaS Market Research Marketing Platform Marketing +1

About TokenPig and Digraph.dev

In their own words, as submitted to SaaSHub.

TokenPig
Digraph.dev

TokenPig converts documents into clean, structured Markdown built specifically for LLM and RAG workflows — ChatGPT, Claude, Gemini, and retrieval pipelines. The problem Raw PDF, Word, PowerPoint and Excel exports carry a lot of formatting noise — repeated headers, broken tables, inconsistent...

Read more about TokenPig

Digraph is an AI marketing platform for brands. It brings together AI research, market intelligence, website and campaign analysis, specialist AI workflows, and marketer-led guidance to help teams understand what shapes buyer decisions and what to do next. Teams can measure how AI systems...

Read more about Digraph.dev

Features and specs

What each product offers, as listed by its team.

TokenPig 3 features
Digraph.dev 5 features
  • Supported Formats
    PDF, DOCX, PPTX, XLSX, HTML, CSV, JSON, XML, TXT, MD
  • Token savings estimate
    Shows tokens saved vs. raw document for each conversion
  • Batch processing & API
    Pro/Enterprise plans include batch conversion, ZIP export and a conversion API
  • Developer-focused positioning
    The .dev domain and branding suggest a tool built for developers and technical teams, so its workflows are likely to fit engineering needs better than a generic product. I could not browse the site, so this is inferred from its positioning rather than confirmed.
  • Graph-based approach
    The name 'Digraph' (directed graph) suggests it models information as connected nodes and relationships. That kind of structure can make dependencies, ideas, or decisions easier to see than flat lists or documents. Confirm how the product actually uses this.
  • Modern, minimal presentation
    Newer developer tools tend to have lean interfaces and a focused feature set, which can mean a short learning curve and less clutter. I could not verify this for Digraph, so check it with a trial.
  • Potential for better organization and clarity
    If the tool works as the name suggests, visualizing relationships between items can improve shared understanding across a team. The benefit depends on how well the product is executed.
  • Early-stage responsiveness
    Smaller or newer products often respond quickly to user feedback and let users influence the roadmap. This is a general tendency and has not been verified for Digraph.

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
TokenPig
Digraph.dev
100% 100%
Markdown Converter
0% 0%
0% 0%
Marketing Platform
100% 100%
100% 100%
Document Management
0% 0%
0% 0%
SaaS
100% 100%

Questions & Answers

As answered by people managing TokenPig and Digraph.dev.

What's the story behind your product?

TokenPig's answer

TokenPig started from a recurring frustration: pasting PDF or Word exports into an LLM and watching layout noise — repeated headers, broken tables, stray whitespace — burn through the context window before the actual content even got read. TokenPig was built to solve that specific problem: clean, structured Markdown output plus visibility into the tokens saved.

How would you describe the primary audience of your product?

TokenPig's answer

Two main groups: individuals who regularly feed documents into ChatGPT or Claude and want cleaner, cheaper context (researchers, consultants, students), and developers/teams building RAG pipelines who need reliable document-to-Markdown conversion via API.

What makes your product unique?

TokenPig's answer

TokenPig focuses specifically on token efficiency, not just format conversion. Alongside clean Markdown output, it shows an estimated token savings for every conversion, so users can see exactly how much context window they're recovering before pasting a document into ChatGPT, Claude or Gemini — something general-purpose converters don't surface.

Why should a person choose your product over its competitors?

TokenPig's answer

TokenPig runs entirely in the browser — no Python setup, no libraries to install, no code to maintain. That makes it accessible to non-developers (consultants, researchers, students) while still offering batch processing and an API for teams that want to automate document ingestion at scale.

Who are some of the biggest customers of your product?

TokenPig's answer

  • Independent consultants and researchers preparing documents for LLM workflows
  • Development teams building RAG pipelines

Which are the primary technologies used for building your product?

TokenPig's answer

Built as a modern web application using Next.js and TypeScript, with a focus on fast, reliable document processing entirely server-side — no client installation required.

User comments

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Alternatives to TokenPig and Digraph.dev

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