正在加载视频...

视频加载失败

返回首页

We just made the Warp API and MCP completely free. Most HR platforms make you sit through a sales call and a questionnaire just to reach your own data. We think that's backwards. You can pull your entire company and employee data, time off, compensation, payroll, IT, basically anything...

ayushswrites's profile picture

Ayush S

13,919 subscribers

730,614 次观看 • 3 个月前 •via X (Twitter)

科学技术教育健康养生
LIVE

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Today we are re-introducing Warp, the AI-native employee management platform for payroll, compliance, benefits, HR, and IT that runs itself. We’ve raised $85M to rebuild the last great enterprise software category. We shipped more in the last 3 months than our first two years combined, so we made a video to tell our story and showcase the platform. Warp brings payroll, HR, compliance, IT, and benefits into one platform, from your first hire to your ten-thousandth. Payroll runs on its own, accurate and on time across all 50 states, and in 150-plus countries in local currency. Hire in a new state and Warp registers you with every agency automatically. When a tax notice shows up, Warp reads it, drafts the response, and files it across more than 10,000 jurisdictions. 80% resolve without anyone on your team touching them. The rest go to our in-house tax experts, not back to you. Onboarding runs itself. The moment an offer is signed, agreements, direct deposit, tax forms, benefits, and every account, app, and device get provisioned automatically. The day someone leaves, all of it deactivates in one action. Benefits work the same way. Warp is your licensed broker across every carrier for health, dental, vision, and 401k. You pick the plan. Enrollment, renewals, and every deduction into payroll happen on their own. Revenue has grown 100x in 2 years. 1,200+ companies run payroll, HR, and compliance on Warp. We're on track to process $1.7B in payroll this year. This is just the beginning of what AI-native employee management looks like. We can't wait to build the rest of it with you. Run your company at warp speed:
2:14

Today we are re-introducing Warp, the AI-native employee management platform for payroll, compliance, benefits, HR, and IT that runs itself. We’ve raised $85M to rebuild the last great enterprise software category. We shipped more in the last 3 months than our first two years combined, so we made a video to tell our story and showcase the platform. Warp brings payroll, HR, compliance, IT, and benefits into one platform, from your first hire to your ten-thousandth. Payroll runs on its own, accurate and on time across all 50 states, and in 150-plus countries in local currency. Hire in a new state and Warp registers you with every agency automatically. When a tax notice shows up, Warp reads it, drafts the response, and files it across more than 10,000 jurisdictions. 80% resolve without anyone on your team touching them. The rest go to our in-house tax experts, not back to you. Onboarding runs itself. The moment an offer is signed, agreements, direct deposit, tax forms, benefits, and every account, app, and device get provisioned automatically. The day someone leaves, all of it deactivates in one action. Benefits work the same way. Warp is your licensed broker across every carrier for health, dental, vision, and 401k. You pick the plan. Enrollment, renewals, and every deduction into payroll happen on their own. Revenue has grown 100x in 2 years. 1,200+ companies run payroll, HR, and compliance on Warp. We're on track to process $1.7B in payroll this year. This is just the beginning of what AI-native employee management looks like. We can't wait to build the rest of it with you. Run your company at warp speed:

Ayush S

31,475 次观看 • 2 个月前

Just announced at Retool Summit: A new way to build. Describe the app you want, and Retool generates it instantly. We’re bringing AI AppGen to the enterprise—on your data, in your cloud, with your security built right in.
0:26

Just announced at Retool Summit: A new way to build. Describe the app you want, and Retool generates it instantly. We’re bringing AI AppGen to the enterprise—on your data, in your cloud, with your security built right in.

Retool

1,484,411 次观看 • 11 个月前

Sam Altman: "I think we should be more of a platform company than a product company.” “We just merged ChatGPT and Codex together. So we used to have ChatGPT, Codex, and the API. And Codex, sort of unfortunately named, but that was not just coding, it could do any kind of work, which confused people." “What I think most people want is the single interface to their own personal or their company's AGI that can kind of help them with whatever they need. And then the ability with an API to build anything they want on top of it. And that is the platform that we should offer to the world." “We're going to sell great AI at every point on the cost-performance curve. You want really high end AI to discover science, that's great. You want really inexpensive AI to do a massive amount of volume of work that maybe doesn't require genius level intelligence, we got you covered there too.” “I don't think we should go build every product category. I don't think we should go try to compete with all of our customers. I don't think we should try to subsume the entire economy. I think we should offer this platform and try to have 100 million new businesses and 8 billion people use it in all kinds of new ways."
2:11

Sam Altman: "I think we should be more of a platform company than a product company.” “We just merged ChatGPT and Codex together. So we used to have ChatGPT, Codex, and the API. And Codex, sort of unfortunately named, but that was not just coding, it could do any kind of work, which confused people." “What I think most people want is the single interface to their own personal or their company's AGI that can kind of help them with whatever they need. And then the ability with an API to build anything they want on top of it. And that is the platform that we should offer to the world." “We're going to sell great AI at every point on the cost-performance curve. You want really high end AI to discover science, that's great. You want really inexpensive AI to do a massive amount of volume of work that maybe doesn't require genius level intelligence, we got you covered there too.” “I don't think we should go build every product category. I don't think we should go try to compete with all of our customers. I don't think we should try to subsume the entire economy. I think we should offer this platform and try to have 100 million new businesses and 8 billion people use it in all kinds of new ways."

dnap

322,713 次观看 • 24 天前

Today we're launching Amplitude MCP MCP was made for data analytics. Ask a vague question and have an AI model iteratively query Amplitude to find you insights. Amplitude MCP exposes all of Amplitude's functionality so an agent can interact with it directly. It allows you to use Amplitude without having to know anything about Amplitude's user interface or your data taxonomy. It uses the intelligence of off the shelf AI agents, including Claude, Gemini, and Cursor, to query Amplitude data you already have to find answers. It leverages all of your existing Amplitude data and how it's used to navigate through large complex behavioral datasets. You can have conversations about your product data directly inside any AI model with MCP. It can create Amplitude dashboards and notebooks with what it finds and even make recommendations. This is the best MCP use case I've ever seen. Watching an AI agent think, reason, query Amplitude, and then repeat that process iteratively is magical. See it in action:
3:08

Today we're launching Amplitude MCP MCP was made for data analytics. Ask a vague question and have an AI model iteratively query Amplitude to find you insights. Amplitude MCP exposes all of Amplitude's functionality so an agent can interact with it directly. It allows you to use Amplitude without having to know anything about Amplitude's user interface or your data taxonomy. It uses the intelligence of off the shelf AI agents, including Claude, Gemini, and Cursor, to query Amplitude data you already have to find answers. It leverages all of your existing Amplitude data and how it's used to navigate through large complex behavioral datasets. You can have conversations about your product data directly inside any AI model with MCP. It can create Amplitude dashboards and notebooks with what it finds and even make recommendations. This is the best MCP use case I've ever seen. Watching an AI agent think, reason, query Amplitude, and then repeat that process iteratively is magical. See it in action:

Spenser Skates

32,420 次观看 • 11 个月前

We're currently rebranding APItoolkit to Monoscope (monoscope ). This is because the scope of the platform was beyond API monitoring (Even if it still can do that; 3rd party or own API monitoring). But Monoscope is now a general open telemetry vendor. So, anything that can be instrumented via OpenTelemetry can be monitored using Monoscope. You can also create all sorts of dashboards (and yes, you can use AI to make the charts). And you can have all your data be stored in your own s3 bucket (you own the data. We don't charge for retention), so you can query years of data via the platform. No extra cost. Let me know what you think. Cheers.
4:23

We're currently rebranding APItoolkit to Monoscope (monoscope ). This is because the scope of the platform was beyond API monitoring (Even if it still can do that; 3rd party or own API monitoring). But Monoscope is now a general open telemetry vendor. So, anything that can be instrumented via OpenTelemetry can be monitored using Monoscope. You can also create all sorts of dashboards (and yes, you can use AI to make the charts). And you can have all your data be stored in your own s3 bucket (you own the data. We don't charge for retention), so you can query years of data via the platform. No extra cost. Let me know what you think. Cheers.

Anthony Alaribe {···}

17,825 次观看 • 11 个月前

"Claude Code is the first AI tool that can actually recreate how a data scientist thinks." Here's my new episode with Sumeet Marwaha (Head of Data at Brex) on exactly how to build an AI analyst with Claude Code. We covered: ✅ 3 queries to build a data analyst MCP ✅ How to give the analyst both data + context ✅ Exclusive Brex data on which AI tools are crushing it in startups and enterprise Some quotes from Sumeet: "I've set up dashboards many times in my career. They end up getting ignored. Claude will always read it. Claude will always ask the right questions." "You have to set up Claude Code to not just look at the data. It should be able to search Slack, find the incident, and understand why your metrics look wrong." "This tool is absolutely crushing it based on our data. It's both the startup AND enterprise coding tool of choice." 📌 Watch now:
0:46

"Claude Code is the first AI tool that can actually recreate how a data scientist thinks." Here's my new episode with Sumeet Marwaha (Head of Data at Brex) on exactly how to build an AI analyst with Claude Code. We covered: ✅ 3 queries to build a data analyst MCP ✅ How to give the analyst both data + context ✅ Exclusive Brex data on which AI tools are crushing it in startups and enterprise Some quotes from Sumeet: "I've set up dashboards many times in my career. They end up getting ignored. Claude will always read it. Claude will always ask the right questions." "You have to set up Claude Code to not just look at the data. It should be able to search Slack, find the incident, and understand why your metrics look wrong." "This tool is absolutely crushing it based on our data. It's both the startup AND enterprise coding tool of choice." 📌 Watch now:

Peter Yang

39,600 次观看 • 8 个月前

Introducing PulseAI, where your data is your knowledge. PulseAI Platform is an agent-to-silicon AI infrastructure platform built to keep your data secure and sovereign, enabling the next AI enterprise. Offered in form factors for every stage of enterprise AI, PulseAI enables enterprise from initial pilot to hyperscale. Combining Gruve's AI-native services with NVIDIA-powered GPU architectures, it scales from 16 RTX 6000 PRO to 2,048 B300 GPUs, with security, storage, and compute integrated. The next enterprise is built on its own data and intelligence. We are here to enable it. Book your consultation: Read more on PulseAI from our Chief AI & Technology Officer Matt Robinson:
3:48

Introducing PulseAI, where your data is your knowledge. PulseAI Platform is an agent-to-silicon AI infrastructure platform built to keep your data secure and sovereign, enabling the next AI enterprise. Offered in form factors for every stage of enterprise AI, PulseAI enables enterprise from initial pilot to hyperscale. Combining Gruve's AI-native services with NVIDIA-powered GPU architectures, it scales from 16 RTX 6000 PRO to 2,048 B300 GPUs, with security, storage, and compute integrated. The next enterprise is built on its own data and intelligence. We are here to enable it. Book your consultation: Read more on PulseAI from our Chief AI & Technology Officer Matt Robinson:

Gruve

66,390 次观看 • 3 个月前

Today we introduced Gemini Enterprise, built with our most advanced Gemini models. It allows you to chat with your company’s documents, data and apps as well as build and deploy AI agents, all grounded in your information and context. Have a look at how it helps you build an agent for almost anything:
0:37

Today we introduced Gemini Enterprise, built with our most advanced Gemini models. It allows you to chat with your company’s documents, data and apps as well as build and deploy AI agents, all grounded in your information and context. Have a look at how it helps you build an agent for almost anything:

Sundar Pichai

1,105,954 次观看 • 11 个月前

Sierra agents can be published on your web site, integrated with your mobile app, answer the phone - and now they can also be published to ChatGPT so you can directly reach hundreds of millions of consumers with your agent. Since OpenAI announced ChatGPT apps two weeks ago, we've heard from our customers that they want two things: a direct customer relationship and the ability to reach customers where they already are. We don't think you should have to choose. With Sierra, you can build once and run everywhere. Here's a demo of an agent I built to show how it works. And our blog post is here:
2:59

Sierra agents can be published on your web site, integrated with your mobile app, answer the phone - and now they can also be published to ChatGPT so you can directly reach hundreds of millions of consumers with your agent. Since OpenAI announced ChatGPT apps two weeks ago, we've heard from our customers that they want two things: a direct customer relationship and the ability to reach customers where they already are. We don't think you should have to choose. With Sierra, you can build once and run everywhere. Here's a demo of an agent I built to show how it works. And our blog post is here:

Bret Taylor

55,607 次观看 • 10 个月前

Today we're launching Hebbian Robotics (YC S26) Hebbian Robotics (YC S26) . We build APIs for evaluating data quality, without training a robotics model. Data vendors use our API to search and analyze Physical AI data at scale, getting on-demand quality signals and metrics without managing infrastructure. High-quality data is the bottleneck to the next frontier of intelligence in robotics. Buyers want data they can trust. Data providers are focused on operational excellence. They don't have the bandwidth to understand the quality of their data at scale. We're fixing this. Vendors use our APIs to understand the impact of their decisions on their data quality: - Buyers demanding per-collector hour limits? Prove compliance while we stay ahead of the workarounds. - Changed your collection SOPs? Monitor for quality drift and regression. - Suspect duplicate samples? Verify with a single API call. Before Hebbian, I trained AI models for industrial cleaning robots, and Kingston Kuan spent years building large-scale infrastructure at Jane Street.
2:17

Today we're launching Hebbian Robotics (YC S26) Hebbian Robotics (YC S26) . We build APIs for evaluating data quality, without training a robotics model. Data vendors use our API to search and analyze Physical AI data at scale, getting on-demand quality signals and metrics without managing infrastructure. High-quality data is the bottleneck to the next frontier of intelligence in robotics. Buyers want data they can trust. Data providers are focused on operational excellence. They don't have the bandwidth to understand the quality of their data at scale. We're fixing this. Vendors use our APIs to understand the impact of their decisions on their data quality: - Buyers demanding per-collector hour limits? Prove compliance while we stay ahead of the workarounds. - Changed your collection SOPs? Monitor for quality drift and regression. - Suspect duplicate samples? Verify with a single API call. Before Hebbian, I trained AI models for industrial cleaning robots, and Kingston Kuan spent years building large-scale infrastructure at Jane Street.

Brandon Ong

166,528 次观看 • 1 个月前

every question in this clip is an ownership question, especially data because when everyone has access to the same intelligence, the only input that separates your business from the next one is the data you own your data is decades of decisions, customers, mistakes, and edge cases that exist nowhere else on earth that is the moat and enterprises are waking up to the fact that they've been leaking it one api call at a time my prediction is this: data ownership is going to absolutely matter in the world we're going into and whoever's building the infrastructure for it is going to have a very good decade.
0:48

every question in this clip is an ownership question, especially data because when everyone has access to the same intelligence, the only input that separates your business from the next one is the data you own your data is decades of decisions, customers, mistakes, and edge cases that exist nowhere else on earth that is the moat and enterprises are waking up to the fact that they've been leaking it one api call at a time my prediction is this: data ownership is going to absolutely matter in the world we're going into and whoever's building the infrastructure for it is going to have a very good decade.

Adeniyi.sui

13,834 次观看 • 2 个月前

Your AI Agents can only analyze 1GB of data Enterprises have 1,000,000x as much data We fixed that... It took 3 years and building an entirely new execution environment to pull this off. TextQL lets AI agents analyze your ENTIRE enterprise data - not just the 0.0001% they can handle today. Here's what makes it so different: 1. ALL your data, not samples. AI today: 1GB demos. Your reality: 350TB across 47 systems. TextQL: Everything. At once. 2. Real enterprise questions.ChatGPT writes poems. We answer why renewal rates dropped 3% after ERP upgrades. 3. No more sandbox limitations.Everyone else: Jupyter notebook with 10GB RAM. Us: A data center. ------------------------------ In 2021, I watched Fortune 500s spend millions on AI that could only analyze data that fits on a USB stick. Today: - We process 10+ petabytes daily - Our biggest customer analyzes 100TB in real-time - Average query spans 50+ data sources And we just proved what everyone said was impossible - AI that can actually build a digital twin of your enterprise ------------------------------ To celebrate, we're giving away free data architecture assessments. We'll show you exactly how much of your data is invisible to AI right now (spoiler: it's probably 99.9%). Comment "TextQL" and we'll send you the assessment link.
1:09

Your AI Agents can only analyze 1GB of data Enterprises have 1,000,000x as much data We fixed that... It took 3 years and building an entirely new execution environment to pull this off. TextQL lets AI agents analyze your ENTIRE enterprise data - not just the 0.0001% they can handle today. Here's what makes it so different: 1. ALL your data, not samples. AI today: 1GB demos. Your reality: 350TB across 47 systems. TextQL: Everything. At once. 2. Real enterprise questions.ChatGPT writes poems. We answer why renewal rates dropped 3% after ERP upgrades. 3. No more sandbox limitations.Everyone else: Jupyter notebook with 10GB RAM. Us: A data center. ------------------------------ In 2021, I watched Fortune 500s spend millions on AI that could only analyze data that fits on a USB stick. Today: - We process 10+ petabytes daily - Our biggest customer analyzes 100TB in real-time - Average query spans 50+ data sources And we just proved what everyone said was impossible - AI that can actually build a digital twin of your enterprise ------------------------------ To celebrate, we're giving away free data architecture assessments. We'll show you exactly how much of your data is invisible to AI right now (spoiler: it's probably 99.9%). Comment "TextQL" and we'll send you the assessment link.

ethan ding 📊

162,180 次观看 • 1 年前

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.
1:21

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 • 1 年前

herdr isn't an app. that's by design. it's a runtime for your coding agents. it owns your terminals, your agents, their state, and lets you drive them from anywhere. that was the idea from day one. but people started running with it faster than we could give them a real way to. even without any official support, they're already building on top of it. web, ios, dashboards. their own idea of what a client even is. so here's a sneak peek 👇 it's native api support in the runtime, the thing we've been building so you can. the tui will always be the first citizen. but soon you'll be able to build your own client on top of herdr, on the same protocol we do.
0:23

herdr isn't an app. that's by design. it's a runtime for your coding agents. it owns your terminals, your agents, their state, and lets you drive them from anywhere. that was the idea from day one. but people started running with it faster than we could give them a real way to. even without any official support, they're already building on top of it. web, ios, dashboards. their own idea of what a client even is. so here's a sneak peek 👇 it's native api support in the runtime, the thing we've been building so you can. the tui will always be the first citizen. but soon you'll be able to build your own client on top of herdr, on the same protocol we do.

herdr

60,487 次观看 • 2 个月前

I just inscribed the CRAWL module to Termina! You can now crawl the OCI to find Bitmap districts with reinscriptions or children! GO TO: TRY: > crawl bitmap This will take a long time, but don't worry! I already did it for you. Bring your own data: Let's work together to keep this dataset updated. You can crawl ranges (for example, of your own bitmaps) and submit a pull request. It took me about 7 hours to crawl all of bitmap with about 15 windows open each running on a range. It would've taken about 10 days with just one window! Definitely some improvements that can be made in performance for the future, but so now we have at least made it possible! And it is mind-blowing what we will be able to do with this data. Stay tuned later this week to find out how we can piggyback off this data to build powerful tools on-chain!
2:05

I just inscribed the CRAWL module to Termina! You can now crawl the OCI to find Bitmap districts with reinscriptions or children! GO TO: TRY: > crawl bitmap This will take a long time, but don't worry! I already did it for you. Bring your own data: Let's work together to keep this dataset updated. You can crawl ranges (for example, of your own bitmaps) and submit a pull request. It took me about 7 hours to crawl all of bitmap with about 15 windows open each running on a range. It would've taken about 10 days with just one window! Definitely some improvements that can be made in performance for the future, but so now we have at least made it possible! And it is mind-blowing what we will be able to do with this data. Stay tuned later this week to find out how we can piggyback off this data to build powerful tools on-chain!

bitoshi blockamoto 🧱 BITMAP 🟧

23,686 次观看 • 11 个月前

Yesterday I met with a $100M brand completely swamped trying to build AI agents. They were duct taping together N8n, Gumloop, Make, Lindy and Zapier hoping it would help automate. Here’s the thing: Those tools are great but only if your data is clean, connected, and actually usable by AI. For example you can’t build a real media buying agent if it doesn’t know: – What’s in stock – What your customers LTV – How your sales change by season Triple Whale brings all of your data into one place. So when you ask our AI a question, it doesn’t guess because it already has the data. And it knows how to use it. We’ve spent 920 days and hired 72 full-time engineers to build the most advanced data layer in ecom designed for AI from day one. Wallaroo Media figured it out👇 They dropped every other platform for Triple Whale. ❌ No more scattered agents ❌ No more platform-hopping ✅ Better answers, better automations, better results Shout out to Justin Doyle and the whole Wallaroo team for the incredible partnership!
1:09

Yesterday I met with a $100M brand completely swamped trying to build AI agents. They were duct taping together N8n, Gumloop, Make, Lindy and Zapier hoping it would help automate. Here’s the thing: Those tools are great but only if your data is clean, connected, and actually usable by AI. For example you can’t build a real media buying agent if it doesn’t know: – What’s in stock – What your customers LTV – How your sales change by season Triple Whale brings all of your data into one place. So when you ask our AI a question, it doesn’t guess because it already has the data. And it knows how to use it. We’ve spent 920 days and hired 72 full-time engineers to build the most advanced data layer in ecom designed for AI from day one. Wallaroo Media figured it out👇 They dropped every other platform for Triple Whale. ❌ No more scattered agents ❌ No more platform-hopping ✅ Better answers, better automations, better results Shout out to Justin Doyle and the whole Wallaroo team for the incredible partnership!

Maxx Blank 🐳

47,007 次观看 • 1 年前

YOUR AI AGENT CAN NOW COLLECT DATA FROM ALMOST ANY WEBSITE X, YouTube, Reddit, random websites, basically whatever you need for research, analytics or monitoring. Here are 3 GitHub tools that let your agent pull the data for you. 1. Agent-Reach Bundles tools for working with different platforms in one place. X, YouTube, Reddit, GitHub and more. 2. Patchright Enhanced Works through the browser with Playwright. You can listen to the requests a website makes and pull the data you need through a script. So if a website doesn’t have a proper API, you still have a way to get the data. 3. Scrapling A general purpose tool for pulling data from web pages. And the best part is that you can give all of this to your AI agent. For example: “Collect posts from 100 X accounts from the last month, find the most popular topics and analyze what’s working.” Or: “Collect reviews about this product from Reddit and YouTube and summarize the main complaints.” You tell the agent what data you need → it writes the code → collects the data → gives you the result. Basically, you’re giving your agent the ability to pull data from almost anywhere on the web. That opens up a whole different level of stuff you can automate.
0:41

YOUR AI AGENT CAN NOW COLLECT DATA FROM ALMOST ANY WEBSITE X, YouTube, Reddit, random websites, basically whatever you need for research, analytics or monitoring. Here are 3 GitHub tools that let your agent pull the data for you. 1. Agent-Reach Bundles tools for working with different platforms in one place. X, YouTube, Reddit, GitHub and more. 2. Patchright Enhanced Works through the browser with Playwright. You can listen to the requests a website makes and pull the data you need through a script. So if a website doesn’t have a proper API, you still have a way to get the data. 3. Scrapling A general purpose tool for pulling data from web pages. And the best part is that you can give all of this to your AI agent. For example: “Collect posts from 100 X accounts from the last month, find the most popular topics and analyze what’s working.” Or: “Collect reviews about this product from Reddit and YouTube and summarize the main complaints.” You tell the agent what data you need → it writes the code → collects the data → gives you the result. Basically, you’re giving your agent the ability to pull data from almost anywhere on the web. That opens up a whole different level of stuff you can automate.

TeddyCEO

158,869 次观看 • 2 天前

Gusto cofounder Edward Kim says today is the most important day in Gusto's history since launch. They just shipped Gusto Cofounder, an AI agent that you talk to through texting and Slack that automates almost everything a small business does in its back office. He explains: "We start with all the problems that we're already helping our customers with — payroll, benefits, HR, scheduling — then we bring on a lot of the power of AI into it." "You tell us what your business processes are, starting with payroll, benefits, and all these things we're already doing for you. And Gusto Cofounder will basically run your business process for you." "You communicate with it through SMS and Slack. You don't really even interface with it through a website." "And we connect to all the systems that you're using outside of Gusto as well. Notion, QuickBooks, Google Workspace... Gusto Cofounder brings it all together into one place where it automates your business processes."
4:07

Gusto cofounder Edward Kim says today is the most important day in Gusto's history since launch. They just shipped Gusto Cofounder, an AI agent that you talk to through texting and Slack that automates almost everything a small business does in its back office. He explains: "We start with all the problems that we're already helping our customers with — payroll, benefits, HR, scheduling — then we bring on a lot of the power of AI into it." "You tell us what your business processes are, starting with payroll, benefits, and all these things we're already doing for you. And Gusto Cofounder will basically run your business process for you." "You communicate with it through SMS and Slack. You don't really even interface with it through a website." "And we connect to all the systems that you're using outside of Gusto as well. Notion, QuickBooks, Google Workspace... Gusto Cofounder brings it all together into one place where it automates your business processes."

TBPN

58,412 次观看 • 3 个月前

i wish i could just upload a CSV and it would automatically create a dashboard so we built this today we're launching graphed .com graphed is an AI data analytics and dashboard generator upload data into Graphed and it's gonna one shot generate a dashboard you can chat with the entire dashboard to make changes and you can click into the graph and chat with it to make updates everything you create in Graphed can easily be shared with your team by sending a link or you can download a screenshot and drop it into a Slack channel or add it to a presentation the Graphed source data can either be a CSV or a data integration data integrations allow you to create live dashboards that are constantly updating in the background we're launching with Google Analytics 4 as our first data integration but we have Shopify, Facebook ads, Google Ads, MongoDB, and hundreds more are on our product roadmap you can sign up for free at graphed .com and if you want a 40% discount code that will only be available during launch comment "graphed" below
0:52

i wish i could just upload a CSV and it would automatically create a dashboard so we built this today we're launching graphed .com graphed is an AI data analytics and dashboard generator upload data into Graphed and it's gonna one shot generate a dashboard you can chat with the entire dashboard to make changes and you can click into the graph and chat with it to make updates everything you create in Graphed can easily be shared with your team by sending a link or you can download a screenshot and drop it into a Slack channel or add it to a presentation the Graphed source data can either be a CSV or a data integration data integrations allow you to create live dashboards that are constantly updating in the background we're launching with Google Analytics 4 as our first data integration but we have Shopify, Facebook ads, Google Ads, MongoDB, and hundreds more are on our product roadmap you can sign up for free at graphed .com and if you want a 40% discount code that will only be available during launch comment "graphed" below

Cody Schneider

47,333 次观看 • 1 年前