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Baseer
A vision-language model that outperforms GPT-5 on Arabic OCR
Baseer is a vision-language model built specifically for Arabic documents it outperforms GPT-5, Gemini 2.5 Pro, and Azure Document Intelligence on OCR benchmarks. Extracts text, tables (HTML), and equations (LaTeX) while preserving structure. API, on-prem, or web.
Hey PH
Arabic OCR has always been a hard problem for AI: connected script, complex ligatures, right-to-left layout, diacritics most vision-language models (including frontier ones) still struggle with it. We built Baseer to fix that: a specialized vision-language model trained on ~750K pages specifically for Arabic documents.
We benchmarked it against GPT-5, Gemini 2.5 Pro, Azure Document Intelligence, Qwen2.5-VL, and DeepSeek-OCR Baseer came out ahead on every metric (WER, CER, BLEU, CHRF, TEDS). [Link to research paper]
What it does beyond plain text extraction:
Converts tables into clean HTML
Extracts math/scientific equations as LaTeX
Correctly formats classical Arabic poetry (preserving meter/rhyme structure)
Detects watermarks and image placement
Outputs directly to Markdown, Word, or PDF
Available via API for automation, as a web app, or fully on-prem for teams that can't send documents to the cloud. Your files are never stored or used for training.
We benchmarked it against GPT-5, Gemini 2.5 Pro, Azure Document Intelligence, Qwen2.5-VL, and DeepSeek-OCR — Baseer came out ahead on every metric (WER, CER, BLEU, CHRF, TEDS).
Full research paper: https://arxiv.org/abs/2509.18174
Would love feedback, especially from anyone who's tried building OCR/document-AI for low-resource or complex-script languages. AMA!
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About Baseer on Product Hunt
“A vision-language model that outperforms GPT-5 on Arabic OCR”
Baseer was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #148 on the daily leaderboard. Baseer is a vision-language model built specifically for Arabic documents it outperforms GPT-5, Gemini 2.5 Pro, and Azure Document Intelligence on OCR benchmarks. Extracts text, tables (HTML), and equations (LaTeX) while preserving structure. API, on-prem, or web.
Baseer was featured in SaaS (43.6k followers), Developer Tools (517.5k followers) and Artificial Intelligence (475.9k followers) on Product Hunt. Together, these topics include over 245.2k products, making this a competitive space to launch in.
Who hunted Baseer?
Baseer was hunted by Rawan Tattan. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Rawan Tattan