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

Shawkat Kabbara

Maker

📌

3mo ago

Kirill Belov

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

Amir

@kirill_a_belov Yes exactly. That is why we automatically retrieve the relevant pieces of context and pass it to the AI model within it's context limits. Rather than giving it a 100,000 pages of text and Slack conversations, we pick the most relevant pieces for the user's prompt and add it to the context.

This method isn't unique but really hard to get right. The best models have near 50% retrieval accuracy - that means they are able to find the relevant pieces of context 50% of the time. Our model is 86% accurate, which is what makes Papr unique.