---
title: Docs & PDFs
description: Exploring Notion's AI workspace features for team productivity
source: ManticsCore
kind: intent_session
url: https://manticscore.com/clip/s-4db3589c620d9838
---

# Docs & PDFs

Exploring Notion's AI workspace features for team productivity

# Docs & PDFs
7 sources, one thread

Exploring Notion's AI workspace features for team productivity

# Notion
The AI workspace that works for you.

Build Custom Agents, search across all your apps, and automate busywork. The AI workspace where teams get more done, faster.

## Related reading
- [Replit – Build apps and sites with AI](https://replit.com) — replit.com
- [Beautiful UI — Crafted primitives for AI-native interfaces](https://www.beautifului.dev) — beautifului.dev
- [yc-software/qm](https://github.com/yc-software/qm) — github.com

# Google Sheets
Create online spreadsheets with Google Sheets. Collaborate in real-time from any device and leverage AI to generate formatting, analysis, and more.

A powerful tool within Google Workspace designed for real-time collaboration and AI-driven data analysis.

# Airtable
Build Enterprise-ready AI Workflows, Apps & Agents

500,000+ brands use Airtable to enable real-time collaboration, automate repetitive tasks & manual work, and streamline business processes in minutes.

# Coda
Your all-in-one collaborative workspace.

Coda is an all-in-one platform that blends the flexibility of docs, structure of spreadsheets, power of applications, and intelligence of AI.

# Confluence: AI Workspace for Knowledge & Collaboration
Accelerate projects with Confluence, your AI-powered team workspace.

Draft, summarize, and share knowledge to keep work moving faster with Confluence's AI-powered features.

# Department of Defense Budget Request
FY 2026 Budget Proposal

This document outlines the Department of Defense budget request for the 2026 fiscal year, detailing proposed funding and strategic priorities.

# SAOT: Self-Supervised Continual Graph Learning
A novel framework using Structure-Aware Optimal Transport to preserve global relational structures across sequential tasks in graph representation learning.

Existing self-supervised CGL methods often optimize nodes in isolation, failing to maintain global relational structure. SAOT leverages optimal transport theory and cross-task knowledge distillation to prevent inter-node correspondences from distorting during continual learning.

**Key Performance Gains**

- Improves average accuracy by up to 5% on CoraFull-CL
- Improves average accuracy by over 15% on Products-CL
- Outperforms existing self-supervised baselines in Class-IL settings

Full interactive version: https://manticscore.com/clip/s-4db3589c620d9838