Eidesis

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Eidesis

Eidesis

@eidesis_ai

The conversion OS that turns any website into a self-improving revenue engine

เข้าร่วม Mayıs 2026
29 กำลังติดตาม313 ผู้ติดตาม
Eidesis
Eidesis@eidesis_ai·
We are launching Eidesis: the conversion OS that turns any website into a self-improving revenue engine. Today, website optimization is still a manual loop: dashboards, guesses, variants, and weeks of A/B testing. Eidesis turns that into an agentic conversion loop. It learns from real visitor behavior, runs simulations with thousands of synthetic visitors, finds the website changes most likely to lift conversion, runs A/B tests, and auto rolls out the winning versions. A/B testing should be faster and less wasteful. Every website should be able to observe, simulate, test, learn, and continuously roll out higher-converting versions. Book a demo or join the waitlist now ↓
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Eidesis
Eidesis@eidesis_ai·
@joshsum_ appreciate it!! websites are about to get a lot smarter 👀
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Eidesis
Eidesis@eidesis_ai·
@Selinaliyy thank you!! the team has been cooking!😍
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Eidesis
Eidesis@eidesis_ai·
@_ImHayleyJailed hahaha love that, excited to show you what we’re building!
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Hayley Y
Hayley Y@_ImHayleyJailed·
@eidesis_ai Booked a demo mostly out of curiosity but the product looks more serious than i expected tbh
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Eidesis
Eidesis@eidesis_ai·
@Nana_lanxi thank you!! excited to finally share what we’ve been building 🫶
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Eidesis
Eidesis@eidesis_ai·
@K07145991 Haha it’s a big claim, but we mean it very literally. Eidesis observes visitor behavior, finds where conversion breaks, generates better variants, tests them, and learns from the results so the site keeps improving over time.
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Nora Platt
Nora Platt@K07145991·
@eidesis_ai "self-improving revenue engine" is doing a lot of heavy lifting in that sentence lol
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Eidesis
Eidesis@eidesis_ai·
Exactly. The speed of the campaign and the speed of experimentation are completely out of sync right now. We’re trying to make the loop much faster: simulate first, test the highest-signal variants, then learn from real traffic without waiting weeks just to know what was worth trying.
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SallyThreads
SallyThreads@tabibitomasashi·
@eidesis_ai Weeks of A/B testing is the part that kills me every time. by the time results are significant the whole campaign has moved on
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Eidesis
Eidesis@eidesis_ai·
@Lare_teleginski This is exactly the loop we’re trying to close. The goal is to make experiment setup, variant generation, testing, and rollout feel continuous instead of this fragile multi-week process where one page change can invalidate everything. Would love to show you what we’re building.
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Mikael Holm
Mikael Holm@Lare_teleginski·
@eidesis_ai used to spend two weeks just setting up the test, another two waiting for significance, then someone would change the page anyway and invalidate everything. if this actually closes that loop it's worth a demo
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Eidesis
Eidesis@eidesis_ai·
@Maximum41622907 Great question! We don’t ship changes to 100% just because the agent likes them. A variant only gets rolled out after it shows stat sig improvement in an A/B test. The simulation layer helps decide what’s worth testing first; rollout still depends on real traffic performance.
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Griffin Thorn
Griffin Thorn@Maximum41622907·
@eidesis_ai Agentic conversion loop that auto rolls out winners sounds great until a bad test gets shipped to 100% of traffic. what's the rollback mechanism here
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Eidesis
Eidesis@eidesis_ai·
@ammadeth thank you!! exactly, making agentic experiment infra accessible to every team is a huge part of the vision
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Ammad Hassan
Ammad Hassan@ammadeth·
@eidesis_ai Woah this is definitely bringing costly tools down to all developers such as a b experiment infrastructure! Great work
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Eidesis
Eidesis@eidesis_ai·
@rowanzhou thank you rowan!! insane is what we’re going for hahaha!
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Rowan Z
Rowan Z@rowanzhou·
@eidesis_ai congrats for the launch! self-improving revenue engine is insane
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Eidesis@eidesis_ai·
@dear_kxtie ahh thank you! excited to finally get it out there
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Eidesis
Eidesis@eidesis_ai·
@primeireles2010 great question. bit of both: broad model for the prior, your own site for the calibration. the whole trick is making sims that look like your visitors, not generic ones. happy to go deeper
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fabiolr_
fabiolr_@primeireles2010·
@eidesis_ai how does the synthetic visitor simulation actually work? are you training on behavioral data from the site itself or pulling from some broader model?
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