Normain is an extraction-first AI for complex documents. It delivers structured, traceable insights grounded in source material - designed for validation and reuse, not chat-based summaries that hallucinate.
I’m Sara, Co-founder & CEO of Normain: AI built for experts to get structured, verifiable insights from complex documents. AI for extraction, not conversation.
The problem
As a former BCG consultant, I spent more time searching, cross-checking, and validating documents than doing actual analysis.
Chat-based AI didn’t help.
🛑 Answers hallucinated.
🛑 Nuance was missed.
🛑 Nothing was traceable back to source documents.
The solution
What if AI wasn’t optimized for conversation, but for extraction?
That’s what Extractional AI is: AI that turns complex documents into structured, repeatable, and source-verifiable insights you can actually trust.
How it works:
Upload your files and links
Define the insights you want to extract
Extract insights, validate & export
Why use Normain?
Trust and transparency: Every insight is traceable to the exact document, page, and paragraph. Normain structures validation so you can correct and rerun individual insights and clearly see what’s validated, uncertain, or missing.
User-friendly for domain experts: Built for professionals, not prompt engineers. No training required. Business teams in fields like audit, assurance, sustainability, and risk can start immediately.
Deep cross-document analysis: Normain analyzes PDFs, Excel files, PowerPoints, and links using encoded expert judgment, allowing it to understand nuance, context, and critical details across documents.
Built to scale: Reuse the same setup across teams or run the same extraction across multiple companies, clients, or data rooms at once.
👉 Sign up for free here, and if you comment with your use case, I’ll personally suggest how to set up your first extraction 🚀
The positioning around "Extractional AI" as a new category is a bold bet. Curious how you plan to distribute this beyond the consulting/audit niche, because the free tier + "publish extractions" model sounds like it could work as a marketplace play but that requires serious supply-side traction first.
Sara and Dennis,
This is a very impressive tool. I tested it from a research perspective and I must say I’m genuinely impressed. Well done.
I haven’t identified any areas for improvement so far, but I’ll continue exploring and will share feedback if anything comes up. For now — congratulations on a great achievement!
The "extraction-first" mindset really resonates — I've had the exact same frustration with chat-based AI for document analysis. The Trust Panel with source traceability sounds crucial for any serious use case. Curious about scalability: if I'm analyzing 50+ documents at once (like in due diligence), how does Normain handle performance and memory? Does it maintain the same level of detail across all files?
On Chrome browser, As soon as the document is uploaded, the progress bar stays stuck at 0% and doesn't advance.
As someone who’s spent time digging through dense docs, the validation and cross-checking overhead is very real.
Extracting insights from messy docs is always a pain. Is this RAG-based or something more custom for the accuracy part?
Congrats on the launch! Optimizing AI for extraction and traceability rather than conversation feels like the right direction for high-stakes work. How does Normain handle ambiguous or partially conflicting signals across documents, especially when expert judgment is required to decide what should be marked as validated versus uncertain?
Like the problem you solve - would love a mobile app as UI since I surprisingly often need to do this kind of analysis and research on the go.
Amazing, big congrats on the launch @sara_landfors@dennislandfors and hardworking team! Reliability is incredibly important to trust our AI tools especially as knowledge workers. Being in finance, one big obstacle to fully integrate tools has been hallucinations and not fully trusting the accuracy of the date and output. Looking forward to testing more advanced analysis!
Complex documents fail in very specific ways (tables, footnotes, scanned PDFs, inconsistent terminology). Which failure modes are you optimizing for first, and how do you measure quality—coverage, citation correctness, numeric fidelity, or something else?
Congrats on the launch! I'm curious about how fast it is. Let's say I have 100 PDF purchase orders and 100 delivery confirmations and I want to cross-check which purchase orders have delivery confirmations that match precisely, and flag any discrepancies (either it was not possible to match the order with a deliver confirmation at all, or the content in the delivery confirmation does not match the purchase order details). How long time would that take, roughly? Could you make that kind of operation and response available in an API?
Totally understand if this is not a use case that fits what you're looking to build! But figured I'll ask 😄 All the best!
@dennislandfors Congrats on the launch! Really nice take on working with complex docs🚀🔥
Always been looking for a tool that helps me out from complex docs and I think Normain just nails it! Nice shot!
Hi Product Hunt 👋
I’m Sara, Co-founder & CEO of Normain: AI built for experts to get structured, verifiable insights from complex documents. AI for extraction, not conversation.
The problem
As a former BCG consultant, I spent more time searching, cross-checking, and validating documents than doing actual analysis.
Chat-based AI didn’t help.
🛑 Answers hallucinated.
🛑 Nuance was missed.
🛑 Nothing was traceable back to source documents.
The solution
What if AI wasn’t optimized for conversation, but for extraction?
That’s what Extractional AI is: AI that turns complex documents into structured, repeatable, and source-verifiable insights you can actually trust.
How it works:
Upload your files and links
Define the insights you want to extract
Extract insights, validate & export
Why use Normain?
Trust and transparency: Every insight is traceable to the exact document, page, and paragraph. Normain structures validation so you can correct and rerun individual insights and clearly see what’s validated, uncertain, or missing.
User-friendly for domain experts: Built for professionals, not prompt engineers. No training required. Business teams in fields like audit, assurance, sustainability, and risk can start immediately.
Deep cross-document analysis: Normain analyzes PDFs, Excel files, PowerPoints, and links using encoded expert judgment, allowing it to understand nuance, context, and critical details across documents.
Built to scale: Reuse the same setup across teams or run the same extraction across multiple companies, clients, or data rooms at once.
👉 Sign up for free here, and if you comment with your use case, I’ll personally suggest how to set up your first extraction 🚀
Appreciate your support and feedback,
Sara