Skippr AI - The live AI employee inside your product, serving every user
byβ’
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.
Replies
EverTutor AI
Congrats on the launch, Sagi! The line about live agents failing when operators can't treat them like actual employees really stuck with me, feels like the kind of lesson you only learn by actually shipping this stuff with real users for a year. Curious how the agent handles context across really long sessions, does memory ever get reset or does it carry the full history forever? Excited to try this on our onboarding flow.
Spun one up in under five minutes and it actually handled a messy onboarding flow without me babysitting it. Surprised how natural the voice interaction felt across languages.
Skippr AI
@slah4jhΒ Thanks a lot Sila - please let me know if anyway we can help!
Spent a few minutes with the demo agent and it actually clicked through screens like a real person would, not just scripted clicks. The multilingual response felt surprisingly natural too.
Skippr AI
@feride153647Β Thank you for actually spending the minutes π "Like a real person, not scripted clicks" is the whole bet: the agent decides live from what it sees, nothing is pre-recorded. Glad the languages felt natural too, that one took us a while. What would you point it at in your own product?
Embedded it in a quick test and the agent actually remembered context from earlier in the session, which caught me off guard. Browser automation felt snappy too, no lag clicking around the page.
Skippr AI
@abdurrahma55903Β Love that you tested it hands-on Abdurrahman π Funny you picked those two: session memory and action latency were probably the hardest engineering problems of our year. "Caught me off guard" is the reaction we were hoping for. Curious what use case you'd embed it for, and if you push it further, tell me where it breaks.
kinda wild that it actually clicked around my app on its own without me hand holding it, felt like watching a coworker onboard a new hire. honestly the multi language thing surprised me the most, gonna throw a spanish speaking user at it and see
Skippr AI
@feyza1156028Β This made my day Feyza, "watching a coworker onboard a new hire" is exactly the feeling we were chasing π Please do throw the Spanish speaker at it, the agent follows their language mid-session without being asked. Tell me how it goes, and if anything feels off I want to hear that even more.
The right boundary for this kind of product feels like assistance without taking agency away from the user. Let the agent complete obvious setup work, but make its planned action visible before it mutates anything important. That is where trust compounds.
Skippr AI
@krekeltronicsΒ Couldn't agree more Patrick, "trust compounds" is exactly the design principle. The plan is visible before anything runs, the user approves it, watches it happen on their own screen, and can grab the wheel or hit Stop at any point. Agency stays with the user, the agent just removes the labor.
And we see the compounding in real sessions: users start with "show me," and a few minutes in they're saying "just do it." Trust is earned per session, not assumed at install.
Actually impressed by how quickly the agent picked up on my screen during onboarding, felt almost like having a coworker guiding me. Wish the free credits went a tiny bit further but solid first impression.
Skippr AI
@muhammed592898Β Thanks @muhammed592898 for the feedback. Please DM me - would love to increase your trial credits!
One thing that would make this a no-brainer for our team is a Slack or Teams integration where the agent can ping a channel when it gets stuck on something it can't resolve, so a human can jump in without the user having to leave the flow.
Skippr AI
@ecekikardeyzsaΒ coming soon! already have it in Enterprise version
What is the criteria for a problem that would be handed over to a human? Given that Skippr cannot fix it.
Skippr AI
@thomas_digaetanoΒ Good question Thomas. The main criteria: it's outside the agent's knowledge and investigation options (screen, KB, session context), it requires authority the agent deliberately doesn't have (billing decisions, account changes, real bugs), the boundaries the owner set say "not yours to touch," or the user simply asks for a human. In the enterprise version there's also confidence-based handoff, where the agent asks instead of proceeding when it isn't sure.
The part teams like: the handoff comes with the session context, what the user was trying to do, what was checked, where it got stuck. The human starts warm instead of from "hi, how can I help you."
The browser automation is the part I'm most curious about. One thing that would make it feel way more trustworthy is a small audit trail window showing what the agent just clicked or typed, so users can follow along and intervene if it drifts. That kind of transparency would help a lot during onboarding flows where trust is everything.
Skippr AI
@aslhanbukrzy5qΒ Love this β transparency is exactly the design principle we're building around. Today the agent uses a plan-and-approve flow: it shows you what it intends to do before executing, and nothing runs without a green light. A live audit trail during execution (what was just clicked/typed, in plain language, with a pause/take-over button) is the natural next layer, and it's on our radar β especially for onboarding flows where you're right that trust is everything. Really appreciate the thoughtful feedback; this is the kind of input that shapes the roadmap.