Oyeyemi Akinrinade's profile on Product Hunt

About

A solo founder, based in Ontario, Canada. I've spent my career in IT, customer service and security — always customer-facing, always obsessed with trust and privacy. I saw SMBs getting priced out of great support tools, stuck with per-seat taxes and hidden AI markups. So I built Sevidesk: AI-powered support with flat pricing, no per-seat fees, and zero markup on AI. Security-first by design. For growing businesses everywhere. Because support quality shouldn't depend on budget size. It should depend on how much you care.

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Maker History

SevideskScale support with AI — faster, unified, and human at heart

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Joined Product HuntAugust 10th, 2026

Forums

p/sevidesk-ai-powered-customer-support

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3d ago

We're Launching Again on Thursday, 1st October

More great features have been added since the last launch. You can now connect Sevidesk to 9000+ apps via Zapier integrations https://zapier.com/apps/sevidesk... in addition to the native integrations (Shopify, Stripe, Slack and Microsoft Teams). OpenAPI Specification is at https://akinrinadeoyeyemi-source... . New Shopify integration features (Cancel order, Update Tracking, Edit Address) have been added after rigorous reviews by the Shopify App Store teams and Sevidesk is now officially a Shopify Partner. Merchants can now perform these actions, and more, without tabs or context switching. You can now manage billing within the app not just through the Stripe checkout and subscription page.

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1d ago

Sevidesk - Scale support with AI — faster, unified, and human at heart

Sevidesk is AI-powered customer support software with a flat price and no per-seat surprises. AI reply suggestions, live chat bot, ticketing, integrations with Slack, Teams, Stripe, Shopify, and Zapier. Start your 14-day free trial today.

p/openbox

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2mo ago

If your AI agent fails silently, who finds out first?

Imagine an AI agent responsible for routing inbound leads. Nothing crashes. No alerts fire. The workflow keeps running exactly as expected.

The problem is that the agent has slowly started sending high-value leads to the wrong queue. Maybe a few customer issues are being summarized inaccurately. Maybe records are being updated with small mistakes that seem harmless on their own. Each individual error is easy to miss. Over time, though, the impact starts to compound.

Those are the AI failures that interest me most because they rarely look like failures at first. There is no outage, no red warning message, and no obvious signal that something is wrong. The workflow continues operating, but the quality of the outcomes quietly drifts away from what the team intended.

That makes detection a different challenge altogether. It's less about system uptime and more about observation. Are there feedback loops? Quality checks? Escalation paths? Can someone spot a pattern before customers, revenue, or operations start feeling the effects?