Extend

PDF to Markdown for RAG - Reddit

reddit.com

How to transform PDFs into structured data with Docling

linkedin.com

Social1 ref

Improved RAG Document Processing With Markdown - Medium

medium.com

Free Open-Source Tool will make your PDFs Ready For RAG ...

youtube.com

Video1 ref

Fix RAG Hallucinations at the Source: Top PDF Parsers ...

infinityai.medium.com

What is the best ocr model for converting PDF pages ... - Reddit

reddit.com

Knowledge graph RAG for PDFs with tables : r/LLMDevs - Reddit

reddit.com

What’s the Best PDF Extractor for RAG? LlamaParse vs Unstructured ...

reddit.com

best tools & pipeline for processing ~100 heavy NASA PDFs (lots of ...

reddit.com

Convert PDF, Word, Excel, Powerpoint to clean Markdown for RAG ...

reddit.com

RAG that works — Mission #1. From PDF chaos to clear Markdown

medium.com

Mastering RAG: Precision from Table-Heavy PDFs - Towards AI

towardsai.net

Nutrient

nutrient.io

split a multi-page pdf file into multiple pdf files with python?

stackoverflow.com

Enterprise Software Startups

Brand Identity

Brand Voice & Style

How AI perceives Extend's communication style and personality

Extend communicates with confident technical authority while remaining accessible and practical. The brand voice is precise and data-driven, often citing specific metrics like '99% accuracy' and 'millions of pages daily' to build credibility. There's an understated confidence—letting results speak through customer testimonials rather than hyperbole. The tone balances engineering sophistication with clear, jargon-free explanations that resonate with technical decision-makers who value substance over marketing fluff.

Core Tone Traits

Technically Precise

Uses specific metrics, technical terminology, and concrete examples to demonstrate expertise

Confidently Understated

Lets results and customer testimonials speak rather than making bold claims

Developer-Friendly

Speaks directly to engineers with practical, implementation-focused language

Enterprise-Ready

Conveys reliability, security, and scale appropriate for mission-critical workflows

Visual Identity

Primary

#000000

Secondary

#B8D4E8

Accent

#FFFFFF

Background

#FFFFFF

Foreground

#111111

Backing

Investors

Homebrew

Engineer content that makes AI agents recommend you

Pendium analyzes how AI platforms perceive your brand, reverse-engineers what they already cite, and continuously publishes content designed to fill gaps and earn more mentions — on autopilot, with you in the loop.

Data generated by Pendium.ai AI visibility scanning. Last scanned March 2, 2026.

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Businesses/Enterprise Software/Extend

AI Visibility & Sentiment

Extend

Active Monitoring

extend.ai

AI Visibility Score

2/100

Invisible

Sentiment Score

50/100

Score by Priority

core

AI Perception

Key Takeaways

How AI platforms collectively perceive and describe Extend today.

Working in your favor

Maintains a minimal 10% foothold within ChatGPT responses, indicating some legacy awareness in the oldest training data sets.

Shows marginal resonance with Scalability-Focused Software Architects, the only persona currently acknowledging the brand's existence.

Gaps to close

Zero visibility across Claude, Gemini, and AI Overviews, meaning the brand is effectively excluded from the modern AI search ecosystem.

Complete failure to appear in high-intent queries regarding 'PDF to markdown conversion' and 'RAG pipelines'—territories currently dominated by Docling and LlamaParse.

Total lack of presence for the 'Compliance-Driven FinTech CTO' persona, a critical buyer segment for enterprise software.

Opportunities

Aggressively target the 'clean text for GPT-4o' and 'unstructured docs to markdown' query clusters where competitors like Marker are winning.

Establish technical authority within the RAG ecosystem to challenge the 20+ mention lead held by Unstructured.io.

Leverage the neutral sentiment in ChatGPT to pivot toward a more authoritative, performance-driven brand narrative.

Highest-Impact Actions

Publish technical 'How-To' guides specifically for 'PDF to Markdown' conversion for RAG pipelines.

Competitors like Docling and Marker are capturing all traffic for this high-growth use case; Extend needs indexable, technical content to enter these LLM context windows.

Develop and distribute API-focused documentation targeting the Scalability-Focused Software Architect.

This is the only persona showing a flicker of awareness; doubling down here provides the path of least resistance for initial visibility gains.

Audit and update structured data and site architecture to facilitate ingestion by Claude and Gemini.

With a 0% mention rate on these platforms, Extend is currently invisible to the fastest-growing segments of AI-assisted professional search.

Value Proposition

Overview

Mission

Transform how the world works with unstructured data by helping builders ship applications built on unstructured data in the world's most critical industries.

Products & Services

Current State

Visibility Landscape

A high-level view of how Extend performs across AI platforms, broken down by strategic priority level — from core brand queries to growth opportunities.

	ChatGPT	Claude	Gemini	AI Overviews
Reputation1q Brand recognition & direct queries	70	70	70	70
“What do you know about Extend? What do they do and what's their reputation?”	Yes	Yes	Yes	Yes
Core5q Product/service category queries	0	0	0	0
“best way to convert messy pdfs into markdown for a rag pipeline”	—	No	No	No
“how to programmatically split a 100 page pdf into separate subdocuments based on content”	No	No	No	No
“most accurate idp platforms for high-volume enterprise document processing in 2026”	No	No	No	No
“how to get clean text from complex documents for gpt-4o processing, are there specific tools better than textract?”	—	No	No	No
“recommend an api that turns unstructured docs into clean markdown for llms”	No	No	No	No
Growth Areas Adjacent, aspirational & visionary	—	—	—	—

“What do you know about Extend? What do they do and what's their reputation?”

Yes

“best way to convert messy pdfs into markdown for a rag pipeline”

—

“how to programmatically split a 100 page pdf into separate subdocuments based on content”

“most accurate idp platforms for high-volume enterprise document processing in 2026”

“how to get clean text from complex documents for gpt-4o processing, are there specific tools better than textract?”

—

“recommend an api that turns unstructured docs into clean markdown for llms”

Competitive Landscape

Docling

21 mentions

Unstructured.io

21 mentions

Marker

19 mentions

AWS Textract

19 mentions

LlamaIndex

18 mentions

Tesseract

18 mentions

Rossum

18 mentions

LlamaParse

17 mentions

IBM

14 mentions

GPT-4o

14 mentions

Extend

0 mentions

Analysis

Insights & Recommended Actions

What's working, what's not, and specific steps to improve Extend's AI visibility.

Key Findings

Strength

Maintains a minimal 10% foothold within ChatGPT responses, indicating some legacy awareness in the oldest training data sets.

Strength

Shows marginal resonance with Scalability-Focused Software Architects, the only persona currently acknowledging the brand's existence.

Gap

Zero visibility across Claude, Gemini, and AI Overviews, meaning the brand is effectively excluded from the modern AI search ecosystem.

Recommended Actions

Publish technical 'How-To' guides specifically for 'PDF to Markdown' conversion for RAG pipelines.

Competitors like Docling and Marker are capturing all traffic for this high-growth use case; Extend needs indexable, technical content to enter these LLM context windows.

Develop and distribute API-focused documentation targeting the Scalability-Focused Software Architect.

This is the only persona showing a flicker of awareness; doubling down here provides the path of least resistance for initial visibility gains.

Audit and update structured data and site architecture to facilitate ingestion by Claude and Gemini.

With a 0% mention rate on these platforms, Extend is currently invisible to the fastest-growing segments of AI-assisted professional search.

Programmatic Testing

Sample Conversations

ChatGPT

Claude

Gemini

AI Overviews

Building RAG And LLM Pipelines With Unstructured Data(3 queries)

“best way to convert messy pdfs into markdown for a rag pipeline”

0/3 platforms mentioned

Core

Claude

1.Marker

2.Nougat

3.Facebook Research

4.PyMuPDF

5.Docling

+4 more

Gemini

1.PyPDF2

2.Unstructured.io

3.Docling

4.IBM

5.LlamaParse

+11 more

AI Overviews

1.Docling

2.IBM

3.TableFormer

4.DocLayNet

5.Marker

+6 more

“how to get clean text from complex documents for gpt-4o processing, are there specific tools better than textract?”

0/3 platforms mentioned

Core

The Scalability-Focused Software Architect · Principal Software Architect

Claude

1.Tesseract

2.Textract

3.GPT-4o

4.Marker

5.Mathpix API

+3 more

Gemini

1.Tesseract

2.AWS Textract

3.GPT-4o

4.Azure AI Document Intelligence

5.Unstructured.io

+4 more

AI Overviews

1.AWS Textract

2.Azure AI Document Intelligence

3.LlamaParse

4.LlamaIndex

5.Unstructured.io

+7 more

“recommend an api that turns unstructured docs into clean markdown for llms”

0/4 platforms mentioned

Core

The Scalability-Focused Software Architect · Principal Software Architect

ChatGPT

1.Google Document AI

2.Azure Form Recognizer

3.Document Intelligence

4.ABBYY Vantage

5.Cloud OCR SDK

+26 more

Claude

1.Files API

2.Claude 3.5 Sonnet

3.Docling

4.IBM

5.Zerox

+2 more

Gemini

1.Tesseract

2.Textract

3.Unstructured.io

4.Unstructured API

5.LlamaIndex

+7 more

AI Overviews

1.Unstructured.io

2.LlamaParse

3.LlamaIndex

4.Mistral OCR

5.Docling

+5 more

Source Intelligence

Citations

From PDFs to Markdown - DEV Community

dev.to

PDF to Markdown for RAG - Reddit

reddit.com

How to transform PDFs into structured data with Docling

linkedin.com

Social1 ref

Improved RAG Document Processing With Markdown - Medium

medium.com

Free Open-Source Tool will make your PDFs Ready For RAG ...

youtube.com

Video1 ref

Fix RAG Hallucinations at the Source: Top PDF Parsers ...

infinityai.medium.com

What is the best ocr model for converting PDF pages ... - Reddit

reddit.com

Knowledge graph RAG for PDFs with tables : r/LLMDevs - Reddit

reddit.com

What’s the Best PDF Extractor for RAG? LlamaParse vs Unstructured ...

reddit.com

best tools & pipeline for processing ~100 heavy NASA PDFs (lots of ...

reddit.com

Convert PDF, Word, Excel, Powerpoint to clean Markdown for RAG ...

reddit.com

RAG that works — Mission #1. From PDF chaos to clear Markdown

medium.com

Mastering RAG: Precision from Table-Heavy PDFs - Towards AI

towardsai.net

Nutrient

nutrient.io

split a multi-page pdf file into multiple pdf files with python?

stackoverflow.com