Chatbase

We rode the Toronto subway and built an AI agent for the TTC. In under 10 minutes. On a moving train. With phone hotspot wifi. Then we handed it to real commuters and filmed what happened. The TTC has had 30 years to make their customer service better. We had one laptop and a mobile hotspot. If you're a frequent commuter and want to get the latest info on interruptions and delays, try it out: chatbase{dot}co{slash}ttc You can also build a personalized, conversational AI agent for your business, repost this and comment "Chatbase" and we'll send you a code to get a month free on us.

Flying to Paris next week with @chatbase If you are looking for the best AI customer support tool, find me under the Eiffel Tower.

@EHuanglu 24/7 handling works best when the agent is trained directly on the company's knowledge base and can take the right actions consistently. We've seen that setup resolve a good portion of standard inquiries without constant manual work.

this AI agent can handle customer service 24/7 reading emails, solving customer issues, and replying automatically on its own.. you can test for free, check below

@_SinghDeepika Appreciate including us. At this point, the real test for chatbot tools is how they perform when teams need consistent, production-ready results without heavy setup. We've focused on that simplicity while handling real workflows.

𝗨𝗣𝗗𝗔𝗧𝗘𝗗 𝗟𝗜𝗦𝗧 𝗙𝗢𝗥 𝟮𝟬𝟮𝟲 💡 𝗜𝗱𝗲𝗮𝘀 • ChatGPT • Claude • Bing 🌐 𝗪𝗲𝗯𝘀𝗶𝘁𝗲 • 10Web • Durable • Framer ✍️ 𝗪𝗿𝗶𝘁𝗶𝗻𝗴 • Rytr • Jasper • Writesonic 🤖 𝗖𝗵𝗮𝘁𝗯𝗼𝘁𝘀 • Chatbase • SiteGPT • ChatSonic ⚙️ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 • Make • Zapier • Bardeen 🖼️ 𝗜𝗺𝗮𝗴𝗲 • Midjourney • DALL·E • Stable Diffusion 🎥 𝗩𝗶𝗱𝗲𝗼 • HeyGen • Synthesia • Runway 🎨 𝗗𝗲𝘀𝗶𝗴𝗻 • Flair AI • Booth AI • Canva AI 🎵 𝗠𝘂𝘀𝗶𝗰 • Boomy • Amper • Jukedeck 📈 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 • AdCreative • Simplified • Pencil Save 🔖 for later — this stack covers almost everything you need in 2026. Follow @_SinghDeepika for more AI info

Thanks for the mention. We've seen teams move beyond basic FAQ bots to agents that actually resolve customer inquiries at scale, especially when trained properly on docs + actions. The difference shows in fewer tickets and faster resolutions. Curious what use case you're building for most?

@gregisenberg the "watch for where the mouse repeats itself" framework is underrated. most of the best agent use cases come from watching someone do the boring version of the task manually first

friendly reminder: productizing AI agents is the biggest zero-to-one play on the internet right now. step 1 start with the workflow. open someone’s “how-to” loom, watch for any section where the mouse repeats itself for more than 30 seconds. that is your extraction point. i call this step looking for drudge. step 2 add the context. scrape the internal FAQ, the tribal acronyms, the edge-case screenshots that a general LLM will never see. that proprietary mess formatted into plain text or json is your first moat. sometimes you need an audience for this. it helps. usually i create an audience/community to start. step 3 wire up an agent on an LLM or agent platform: claude, gpt-4o, gemini, lindy, string dot com. keep the prompt brutal-simple: “given this context and that input, return this output.” test until the agent’s average response time beats the human baseline by 10×. keep refining prompt, it will get longer, longer and more valuable. never share that prompt with anyone. step 4 wrap the agent in the thinnest UI possible. one drop zone, one action button, one log window that says “done.” hide the settings; hide the model; hide the magic. outcome is the only feature. make a brand people fall in love with. step 5 price the saved hours. take the median hourly cost of the person who used to run the workflow, multiply by the time you shave off each week, and anchor the subscription somewhere south of pain but north of hobby. step 6 ship video proof before a landing page. record old way vs. new way in a split-screen clip; caption it; post it where the operators hang out. every “how did you do that?” reply is a warm lead. you can use platforms like lindy ai etc to do cold dm/email automation. step 7 loop usage back into the context file. new ticket? new edge case? append it. your agent improves without code, and the context corpus becomes asset #2. step 8 layer distribution inside the product. add a quiet “powered by” footer on every output, or trigger a shareable report by default. users spread the gospel while you sleep. step 9 when churn stabilizes and support tickets hit near-zero, bolt on adjacent micro-agents each with its own promise, its own subscription tier, no extra complexity in the UI. step 10 ignore vanity metrics. screenshots of ARR can be faked (and are constantly). My favorite was watching someone screenshot test payments. Literally fake money lol. Anyways, time returned to a paying customer cannot be faked. compound that saved time across niches until you own a stack of invisible employees. you own a portfolio of little products that save people time and you get paid for it. the market for this is in the billions. do this on repeat and you won’t need funding, permission, or glossy charts. you will be free and be creating impact. this is probably one of the biggest opportunities out there.

If you use Shopify and haven’t set up Chatbase yet, this walkthrough is for you. We cover the full setup of adding a powerful AI agent to your store so your customers can find products, get personalized recommendations, add items to their cart, and track their orders without ever leaving the chat. In the video we walk through connecting your Shopify account, setting up product search and cart actions, enabling live order tracking, and deploying directly to your store.

As teams grow, managing access and visibility becomes important. Different users need different levels of control. With that in mind, we’ve introduced Role-Based Access Control and Audit Logs for enterprise workspaces. Enterprise teams can now create custom roles and permissions, control access, reduce accidental changes, and see a clear record of every important action.

@humphreysu8 Yes, use Chatbase to train agents on the actual knowledge source of your business, not reddit threads!

@chatbase remember guys, don't ask tax related questions on chatgpt or you're gonna get dodgy advice from random redditors

It's tax season, and students already have enough to worry about. We went to UofT campus to talk to students about their experience with the CRA and help them understand what's changing. The future of customer support is conversational. Instead of digging through help articles, you just ask a question and get the right answer instantly. Every organization should have a customer facing AI agent co-founder to answer questions instantly and accurately. Link to CRA Agent: lnkd.in/ebsByHZJ

@byjackprice yess this is why we do what we do

@chatbase This is how B2B marketing is done. Solve real problems for people🙌

If you use Zendesk for customer support and haven't set up Chatbase yet, this walkthrough is for you. We cover the full setup steps of adding a powerful AI agent so your team has backup that works 24/7 to resolve what it can, escalates what it can't, and gets smarter with every ticket. In the video: connecting your account, training on your full ticket history, automating ticket creation and escalation, and drafting responses directly inside Zendesk.

The better context your agent has, the faster it can solve problems. Screenshots and images can now be uploaded directly as context for your agent. If a customer has a problem, they can drop a screenshot of what they’re seeing and the agent can understand the issue and resolve it on the spot. Available across chat bubble, agent page, WhatsApp, Instagram, Messenger, and email.

.@Chatbase just turned 3. I started building Chatbase in college when I was deep into AI before chatgpt even launched. I saw early that every business would eventually need an AI agent to talk to their customers. 3 years later: 10,000+ customers. $8M ARR. more enterprise deals closing weekly than we did in the first 2 years combined. And a team I'm very proud of and excited to be working with. A few months ago there was a study saying that most enterprise deployments of AI fail. That hasn't been the case for Chatbase. Customer facing AI agents work. Our customers connect their CRMs, help desk, payment systems, and handle real customer conversations end to end. Production ready. Year 4 is about Chatbase becoming a household name. Every company will need an AI agent for their customers, and more and more of them are going to realize Chatbase is the best choice. Grateful for every customer and teammate who's been part of this.

I swear some founders start companies just to get dates. And then once they finally get one, they keep answering customer questions. Then the steak gets cold and the girl gets mad. Use @chatbase before you go on a date.

As companies grow, maintaining great customer interactions becomes nearly impossible. @Chatbase exists to help you talk to all your customers as you scale.

@bigr_szn Check your inbox!

@chatbase Chatbase

We rode the Toronto subway and built an AI agent for the TTC. In under 10 minutes. On a moving train. With phone hotspot wifi. Then we handed it to real commuters and filmed what happened. The TTC has had 30 years to make their customer service better. We had one laptop and a mobile hotspot. If you're a frequent commuter and want to get the latest info on interruptions and delays, try it out: chatbase{dot}co{slash}ttc You can also build a personalized, conversational AI agent for your business, repost this and comment "Chatbase" and we'll send you a code to get a month free on us.

@Simplifiedworks Check your inbox!

@chatbase Chatbase

@NaureenAhm Check your inbox!

@chatbase Chatbase

@melaninhippie Check your inbox!

@chatbase Chatbase

@RTNToronto Try the agent out at chatbase.co/ttc 😎

#NEW: Toronto tech startup just solved a huge problem for TTC riders!