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Most AI platforms give you automation with no one accountable. When the agent gets it wrong, there's no one to call. Konfide puts verified Experts and Helpers behind AI agents. Accountable, bookable, earning from every session. Built by one person in 7 days. No code. Just prompts.
Konfide
Konfide is an AI agent marketplace where anyone can build and publish AI specialists, back them with real human expertise, and earn from both.
What makes it different:
1- Human oversight built in. Verified experts back agents and earn 25% of revenue.
2- Anyone can build. No code. 5-step wizard.
3- 10% of all revenue donated to independent AI safety research. Subscribers vote on where it goes.
AI and humans working together. Both earning.
The AI + accountable human layer is interesting. But how are “verified experts” actually verified like do you have any credentials, track record or platform reputation?
Konfide
@lak7 Fair challenge. Here is exactly how it works today.
Every expert must connect their LinkedIn profile, verified by the platform. They also can submmit work samples before going live. No LinkedIn, no approval.
The work examples we will improve post beta using AI, we are in early beta so the layer is manual and lean.
What comes next is platform reputation scores, client reviews after sessions, and user reporting if an expert underdelivers. The CSAT feedback loop is already in the roadmap.
It is not perfect yet. But the baseline bar is real.
I think accountability is an issue with AI platforms and if this goes well people will gain higher trust towards agents and assign critical tasks.
I would like to know how will you transition the user from AI to the human expert mid-session?
Konfide
@prateek_kumar28 This is exactly the problem Konfide was built to solve.
The transition works like this. During any AI agent session, there is always a visible 'Get Human Help' button. The user can trigger it at any point. The AI can also trigger it itself when it detects low confidence or a high-stakes decision. It does not wait to be asked.
When escalation happens, the context from the session passes to the human expert. They see what was discussed. The user does not have to repeat themselves or start over. The handoff is the product.
The expert then responds async or books a live call depending on what the situation needs.
On your broader point about trust and critical tasks, you are right. Trust in AI agents will grow in proportion to how accountable the system behind them is. That is why Konfide's architecture has a human authority layer with actual kill switch control, not just a chatbot with a disclaimer. Accountability has to be structural, not cosmetic.
We are early. But that principle is non-negotiable for us.
Ran Konfide through a quick pass, nice execution for a 7-day solo build. A few things worth a look: text contrast is too low in a couple of spots, and some links rely on color alone to stand out (worth adding an underline or other cue for colorblind users). You're missing a few security headers: Content-Security-Policy, X-Frame-Options, and Permissions-Policy. Worth adding as you scale, they stop other sites from framing/embedding yours or accessing device features without asking. Also noticed page load is a bit on the slower side (~2.8s), might be worth a look if you haven't profiled it yet. All quick fixes, not rebuilds. Happy to point to specifics if useful.
Congrats on the launch. The part that stopped me scrolling: a full marketplace with Stripe Connect payouts, escrow logic and LinkedIn OAuth — and you've said none of it was hand-coded, it was all Lovable prompts. I'm an independent researcher looking at how people build real products with AI tools rather than the usual founder-with-a-CS-degree path, so honest question: where did Lovable actually hit a wall for you — was it the escrow/payout logic, the auth, or something more boring like state management? Curious how you got unstuck. Would genuinely love to swap notes on how the build actually went day to day