Papr.ai - AI-native docs with infinite memory

Hi everyone! 👋

I'm Shawkat, the founder of Papr. As someone with ADHD, keeping track of important details and finding the right context when I need it has always been a struggle. When ChatGPT launched, I was excited thinking it might solve this, but it was like hiring a brilliant executive who forgets every conversation they've ever had—even the most advanced AI couldn't maintain context between interactions.

How could it effectively find and remember critical information buried within terabytes of corporate data?

That's why we created Papr — an AI-native workspace that remembers your context and organizes your knowledge so you don't have to.

What makes Papr different?

• State-of-the-art accuracy: We've achieved 86% accuracy on Stanford's STARK benchmark, securing the number one spot on the leaderboard. STARK represent real-world queries vs. simple needle-in-the-haystack benchmarks.

• Connected to your data: Your AI instantly recalls context from Slack, docs, and meetings—creating a unified knowledge base that answers complex questions and grows with your team.

• Document-first workspace: Unlike chat-first platforms, we're building an AI-native document experience with Apple-inspired design. Create and edit documents while AI maintains perfect context—no agent configuration needed. Think Cursor.ai but for collaborative documents with infinite memory.

Here's what teams are building with Papr:

• 📚 Generate Scientific Research: Transform scattered research papers, meeting notes, and experimental data into cohesive academic papers while maintaining perfect context of your methodology decisions and findings.

• 🌐 Build a 360° Customer View: Automatically aggregate and analyze the latest conversations, usage trends, and public information to create a comprehensive view of your customers. Teams can make informed decisions, increase revenue footprint, improve revenue retention, and enhance customer relationships.

• 🔍 Answer Complex Questions: Find the right answers faster by connecting insights across your team's conversations, documents, and decisions - even remembering context from months ago that you forgot existed.

What does this enable?

Imagine being able to extract feature requests from customer conversations and gain insights across all customers instantly. For example, you could easily identify the top problems your customers face or the most requested features during sales calls—tasks that used to take months now take minutes.

Who is it for?

Papr is for anyone drowning in data but struggling to find the insights they need. Whether you're a researcher, a product manager, or someone juggling multiple projects, Papr helps you stay organized and focused.

Why we built it:

We believe that information overload shouldn't hold you back. With Papr, we're creating a future where your AI doesn't just assist—it understands and remembers, so you can focus on what matters most.

We'd love your feedback and support! 🙏

If you have any questions or thoughts, drop them below. We're here to listen and improve. Thank you for checking out Papr, and we can't wait to hear what you think!

Launch Offer (24 Hours Only):

• Pro subscription: $40/month

• First 50 users get 50% off for the first 3 month

• Priority support included

• 7-day risk-free trial

I thing query context for the AI model has prompt limits?

Love the infinite memory concept for easy retrieval! 👍

Hey Product Hunt! 👋 I'm Amir, one of the makers of Papr.ai. When Shawkat shared his ADHD journey, it deeply resonated with me.

During my time at Shopify, I saw how crucial context sharing is for team success. Shopify invested years building and maintaining internal tools to enable their "open context" philosophy. It was worth it. Teams ramped up faster and quality improved even as they rapidly scaled.

The problem When I led product and growth at an edtech unicorn, I tried replicating Shopify’s system but hit a wall. The tools available in the market were hard to configure and fundamentally failed at making context accessible.

Common questions I got were “Why do we need to create a complex database to write a document?" or “Which folder was that document in?”

Tools meant to organize information became the problem themselves.

Enter Papr.ai We built Papr to make sharing and finding context as effortless as browsing Netflix. No complex setup, just add content, and Pen, our AI assistant will:

• Organizes everything automatically

• Connects related memories as you write

• Surfaces memories when needed

It's Early Days We're just getting started. Try it out and tell us: how could we make your team's knowledge work better for you?

Hi Product Hunt! 👋 I'm Rony, one of the makers of Papr. I wanted to share a bit about the technical journey that led us to build what we believe is the most accurate memory and retrieval system available today.

The Technical Challenge When we started building Papr, we discovered that existing retrieval systems weren't cutting it for real-world queries. Most solutions excel at finding exact matches but struggle with nuanced questions that require understanding context and connecting related information. These systems retrieve the right piece of information 56% of the time at best.

Our Breakthrough After months of R&D and years of experience building search and retrieval systems, we developed a novel approach that:

• Achieves 86% accuracy on Stanford's STARK benchmark (vs. the next best model at 56% accuracy)

• Efficiently retrieves context within seconds

• Maintains context across multiple data sources

What This Means for Users This technical foundation enables Papr to:

1. Unlock deeper insights beyond simple Q&A

2. Connect related concepts across different documents and conversations

3. Understand context from past interactions to provide more accurate responses

Real-World Impact We're seeing teams use this capability to:

• Cut research time by 60%

• Reduce duplicate work by automatically surfacing relevant past discussions

• Make better decisions by having complete context at their fingertips

I'd love to hear from the technical folks in the community - what challenges have you faced with existing knowledge management solutions? How are you currently handling context in your AI applications?

#BuildingInPublic #AI #ProductHunt

Amazing tool boos ! I have never ever seen like this great work 👏

Can I try before I pay?

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