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Still spending hours on repetitive work that should’ve been automated by now? Most teams waste valuable time creating documents from scratch, rewriting the same emails, reformatting data, and manually producing content that could be generated in seconds — with the right tools. Meet |Context — The AI Office Suite...

33,734 次观看 • 1 年前 •via X (Twitter)

6 条评论

D-Coder 的头像
D-Coder1 年前

Finally, AI that actually feels like part of the team.

Mobile Scanner 的头像
Mobile Scanner1 年前

Scan any documents, convert images into text, PDF files, etc. 👍

Ismail khan 的头像
Ismail khan1 年前

Amazing share

Vinay Bharambe 的头像
Vinay Bharambe1 年前

Wow really amezing Share

Atul Kumar 的头像
Atul Kumar1 年前

Wow Nice Sharing !

Chidanand Tripathi 的头像
Chidanand Tripathi1 年前

This is awesome

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Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Aaron Levie

91,863 次观看 • 10 个月前

Data teams spend weeks on simple requests. (This AI answers them in minutes.) Most data analysis is repetitive manual tasks. Data teams spend more time on setup than actual analysis. The workflow usually looks like this: → Run some exploratory data analysis in a local Jupyter notebook or environment → Pull data from multiple disconnected sources → Write code from scratch for every analysis → Export static charts that stakeholders can't explore (or wrestle with legacy BI to create a dashboard) → Manually send updates via email or Slack when data changes → Start over for each new request Most teams accept this as "how data analysis works." While business decisions wait for insights. That's where Fabi changes the entire approach. It's a powerful, AI-native platform built for teams that want to boost productivity and supercharge their data workflows. Instead of working on separate tools and manual processes, you collaborate on analysis that automatically delivers insights where teams work. Here's what makes Fabi different: AI-Native Analysis Environment ↳ SQL and Python work together with AI assistance that handles coding and debugging automatically. Smart Automation Workflows ↳ Automatically send AI-powered reports and summaries right where business works in Slack, email, and spreadsheets. Universal Data Integration ↳ Analyze data from files, Google Sheets, Airtable, plus your data warehouse and databases in one place. Collaborative Data Apps ↳ Create interactive dashboards that stakeholders can explore and ask follow-up questions directly. What you can do with Fabi that legacy BI can't: ➟ Send AI-generated insights directly to Slack channels ➟ Automatically email data summaries to stakeholders ➟ Analyze uploaded files without complex ETL processes ➟ Collaborate on analysis like Google Docs for data ➟ Build workflows that push insights to spreadsheets Perfect for teams that want to move beyond the constraints of legacy and increase their impact. Teams using Fabi see immediate results: ✓ Insights delivered in minutes instead of days ✓ Reduced context switching between tools ✓ Stakeholders explore data independently ✓ Workflows automated to save hours of manual work From analysis to automated delivery - all in one AI-native environment. 📌 Try Fabi today: 👉 Follow Fabi.ai and marc for Fabi updates. 🔄 Repost to help other teams streamline data analysis #DataAnalysis #ModernBI #DataOps #InteractiveDashboards #FabiPartnership #SponsoredByFabi

Andrew Bolis

36,504 次观看 • 10 个月前

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yancymin

21,222 次观看 • 1 年前