SaaS ideas your next customers are already looking for
100 SaaS startup ideas for the people who said they'd pay, from agency owners to dentists. Micro SaaS ideas, AI SaaS ideas and B2B SaaS ideas: find yours, build it, sign them up.
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Pain points in business: what people struggle with
Search the problems to solve, as people described them on Reddit and other platforms, in their own words.
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Unreliable PDF to JSON
High-volume PDF extraction pipelines fail to reliably convert dense, inconsistent, and messy documents into accurate structured JSON, breaking downstream AI and RAG systems.
In their words
Roughly one in five needs more than one attempt. Never costed it, because at that price five attempts rounded to nothing.
we need reliable structured JSON output since extraction errors can break downstream processing
I need to extract text and tables from ~5 million scanned PDF forms and output structured JSON.
It can't handle determining page boundaries when I feed it multi-report scans as it starts going off the rails in loops
different documents → structured data → traceable source references → further analysis
our homegrown LayoutLMv3 setup kept dropping table rows on multi-column scans
AI cannot save me from parsing thousands of pages of inconsistently formatted tariff tables.
A 300-page document may be acceptable with a slower converter, but thousands of such documents become impractical.
Struggling with the formatting is a huge waste of time. This slows me down to a crawl so I want to find a solution.
I tried Excel and PowerQuery to get a split working but nothing was consistently working.
the pdf format should be fixed else in most of the tools the extraction logic is either failed or we get incorrect data
it requires maintenance, a lot of maintenance, I have seen similar stack built 1000s of time for different workflow problems, across the industries.
Is there some magical way to avoid fixing pdf parsing code every 2-3 months when ever something small changes?
it was really bare-bones experience that needed a lot of work to get working effectively
RAG and document pipeline developers
Where they talk
- r/Rag
- r/LLMDevs
- r/LocalLLaMA
- r/documentAutomation
- r/LocalLLM
- r/LangChain
- r/AI_Agents
- r/Python
Tools they use today
- Docling
- PyMuPDF
- Claude
- Qwen
- llamaparse
- pdfplumber
- Python
- Excel
Why those fall short
- Traditional OCR only good for free text; structured outputs miss unasked details
- parser messes up tables, headers, footnotes or multi-column text
- Docling gets the grid, loses the semantics; letter-spacing damage in LaTeX
- AI hallucinates numbers or misaligns columns when formatting changes page-by-page
- VLMs fail quietly, get numbers wrong, drop rows, break LaTeX
Map of ideas
Drawing the map…