Skippr AI - The live AI employee inside your product, serving every user
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Real-time agents that see, talk, and operate software. They onboard, activate, and unblock your users. On their own. Skippr agents keep agenda and memory across full sessions, speak 10 languages, and act on screen with built-in browser automation. Fully self-serve: spin up an agent in minutes, embed with 2 lines of code, or share a meeting link. Trained on your knowledge, styled to your brand. 200 free credits to start, no card required. Talk to me for the deeper enterprise version.
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Skippr AI
Hey PH 👋 Sagi here, founder & CEO of Skippr AI (backed by Bessemer Venture Partners and some other cool investors).
In the last year or so we've been obsessed with what happens when an AI agent can actually see your product, talk to your users, and act, live. Not a chatbot in the corner. A real (human-level) presence inside your product.
Here's what we learned: live agents fail when their human operators can't take a step back and treat them like employees. Ones you'd trust alone with your users, customers and internal users too. If the agent is too late to respond, out of context in long sessions, missing subtlety or tone, or needs the "boss" to work for it (updating the knowledge base, babysitting its learning loop), it brings more pain than gain.
So that's what we spent our time fixing.
We've been working with our design partners on our key use cases, such as onboarding and product adoption, and we're busy implementing more of them and building more agent skills. But today is about bringing what we learned to the wider community. We want anyone to be able to spin up, customize, and embed a live agent instantly. From Shopify stores and Lovable/Replit builders to any AI-first startup, just spin up an agent. Two lines of code to embed, or a simple meeting link.
You'll find live AI employees ("Buddies") inside for onboarding, training, demos, and support. But whatever you can imagine doing with a live agent, you can build it for your users or your team's needs.
Start free with 200 credits, startup package from $149. For serious volume or enterprise, come talk to me.
We're around all day. Try it at skippr.ai and tell us what you think.
Sagi & the Skippr team
Serving every user autonomously is the scary part to watch as a founder, not the cool part. When it hits something it doesn't know, what happens, does it say so and pass it up, or guess? I run a hard no-improvising rule in my own product and even with that rule written down I still catch edge cases weekly.
Skippr AI
@vladimir_iudin Great question. Skippr is trained on your knowledge base, call transcripts, and its own vision and experience inside your app. Self-serve users can get quite far alone, and my team helps with deeper training for complex cases. The agent also gets rules to keep.
It's not a script like the old generation (WalkMe, Pendo) and not a video. In our trials we benchmarked it against human product specialists, and the agent already performs better than the majority of them.
On the "doesn't know" moment: every session feeds the learning loop, so the agent keeps getting better on its own. Edge cases always come, you're right, but once one shows up it's covered from then on. No re-scripting, no flow rebuilds, no babysitting. And for enterprise clients we enable human in the loop: when the agent isn't 100% sure, it asks a question instead of proceeding.
Plus guardrails, all configurable per use case: disable actions, require user approval of the plan before anything runs, and the SDK lets you choose which areas Skippr helps with and which it stays out of.
Users get superpowers, and you save on support and success while the business grows. That trade is why our customers moved past this question.
@sagi_shorrer1 The learning loop covering edge cases after they show up once answers most of my worry. Configurable guardrails I'd want to see in practice, "disable actions" is easy to say and hard to actually scope for a messy real workflow. Similar split on my end, self-serve for the easy stuff, a human for anything ambiguous, and where exactly to draw that line is still the thing I get wrong most often.
Netlify
Hey PH fam 👋
Excited to hunt Skippr AI for the global tech and startup community today!
Here’s the shift I think Skippr represents:
Software went self-serve two decades ago, and we quietly accepted the tradeoff. Nobody greets you when you land in a product. Nobody walks you through setup. Nobody notices when you’re stuck on step 3 and about to churn.
We optimized for scale and lost the floor staff.
Skippr puts that layer back. Think Apple Store Genius Bar energy inside your product, instead of a laminated FAQ binder. An agent that’s present in real time and handles onboarding, activation, demos, and support like a person would.
What impressed me when I tested it:
→ It doesn’t just tell users what to click. It clicks. Built-in browser automation means the agent completes actions on screen, which is the difference between a tour guide and a driver
→ It holds agenda and memory across an entire session instead of resetting like most conversational tools
→ Speaks 10 languages out of the box, so your onboarding works in São Paulo as well as it does in San Francisco
→ Setup is genuinely instant. Trained on your docs, styled to match your brand, live in minutes
Sagi and the Skippr team are here all day. Free tier gets you 200 credits to try it, no payment info needed.
Question for the community: as agents get good enough to staff our products, which parts of the user journey should stay human, and which would you hand over first? Curious where people draw the line 👇
I see you support 10 languages with real-time switching. Does the user have to ask to change the language, or can they just start talking in the new language? Also, what if we need specific Asian languages that aren't part of the current 10?
Skippr AI
@chloe42 Just start talking, no need to ask. Within the 10 switchable languages the agent follows the user's lead immediately, mid-session, and switches back if they do.
Beyond those: we support 50 languages in mono mode (the agent runs the whole session in that language), so odds are what you need is already covered. The 10 are our self-serve default for real-time switching, and we're adding more switchable ones prioritized by customer need.
Which languages do you need specifically? I'd add them to our planning discussion. Not promising a date, but this is exactly the signal that shapes the order.
Interesting. How much can I customise Skippr’s appearance? Can I incorporate my own design system?
Skippr AI
@max_smith20 Quite deep, this was a big ask from our design partners. You control the widget style (avatar, strip, or always-on launcher), colors, brand assets, animations, and the voice and personality to match your tone. Our Buddies avatars are optional, plenty of agents run with their company's own face.
So yes, you can bring your design system's look and feel through the appearance settings, self-serve. If you mean deeper, like pixel-level component integration with your own UI kit, that's an SDK conversation, ping me and I'll show you what's possible.
Would love to see what you'd style it into 🙂
This looks useful. Does the agent adjust its pacing if a user skips multiple steps quickly?
Skippr AI
@dhiraj_patel5 Sure, it's not strict on step by step, has the flexibility and context to skip!
How does the agent handle it when a user asks something totally outside what it was trained on? Does it hand off to a human or just say it doesn't know?
Skippr AI
@talhakhalidmtk First, the agent has a lot of skills to investigate before it ever gets to "I don't know": what it sees on the screen, what the user tells it, your knowledge base, and its own memory and context from the session. It's not a rigid script, it's an agent with a brain, making decisions within guardrails and limits.
Within those limits it doesn't invent. If something is truly outside its knowledge, it says so honestly, points the user to the right channel, and steers the session back on track. For enterprise we also support human in the loop, where the agent asks instead of proceeding when it isn't sure.
And every session feeds the learning loop, so an out-of-scope question usually becomes in-scope for the next user who asks.
The two-line embed is genuinely impressive, got it running in under five minutes. The on-screen automation feels surprisingly smooth for a self-serve setup.
the "it clicks, it doesn't just point" part is the interesting bit and also the scary bit. once an agent is actually driving the UI instead of just narrating, what happens on a destructive action, like a delete or a cancel-subscription button, does it always pause for a real confirmation, or is that left up to how the workspace owner configures it?
Skippr AI
@galdayan Great question Gal. Both, layered. Default is consent first: the agent offers before acting, lays out a plan for multi-step tasks, and waits for a clear yes. The user watches it all on their own screen with a Stop button, so there's no "wait, what did it just do" moment.
Beyond that, the workspace owner can set boundaries, and in the enterprise version go further: where the agent can act, where it only guides, and when plan approval is required. For destructive flows, keep it guide-only: it points, the user clicks. They can even set it to zero actions for the entire app.
Fair to call it the scary bit but our rule to solve it is simple: deterministic mechanisms where you need 100%, looser where the action isn't destructive. Most of an app's zones aren't destructive.
@sagi_shorrer1 that's a clean split - deterministic guardrails on the parts that actually matter, judgment everywhere else, rather than trying to make the whole thing 100% safe and ending up mushy everywhere. the "zero actions for the entire app" fallback is a good escape hatch for cautious workspace owners too. thanks for walking through it in detail.
How are you thinking about this vs. the tooltip-tour tools a lot of us already have?
Skippr AI
@james_harrington2 Tours are signage, Skippr is staff. A tooltip plays the same script to everyone, can't answer questions, and gets skipped by the users who end up stuck. Skippr is live: it talks with the user, sees where they are, adapts, and when guiding isn't enough it takes the cursor and finishes the step. No flows to build, no re-recording when your UI changes