Look, when any project steps from testnet to mainnet, it’s not just an upgrade. It’s proof—proof that the idea actually works in the real world. And @mira_network has just done exactly that. On September 26, 2025, they officially launched their mainnet, and along with it, they released their next-generation API. The name is Verified Generate API. In simple words, it’s just as easy to use as OpenAI, but every single output comes with a cryptographic proof. Meaning, you can know whether this answer is actually true or just the AI’s imagination.
When I first saw this thing, honestly, I was a bit shocked. Because the biggest problem with AI has always been hallucination. One model says “Elon Musk sold Tesla,” and you sit there believing it. Mira breaks that output into tiny “atomic claims.” Then thousands of nodes in the network—each running different AI models—vote on them. Only when there’s a supermajority consensus does it issue the certificate. If you pay attention, it’s exactly like a big jury. You won’t trust one witness, but when ten people agree, then you accept it.
Back when it started on testnet, it was doing around 200,000 inferences per day, with about 500,000 users. Now, coming into February 2026, the whole thing is on another level. More than 4.5 million users, 3 billion tokens being verified every single day, and over 7 million queries. Accuracy? 96%. Hallucinations have dropped by almost 90%. These numbers aren’t just sitting in graphs—they’re actually running live in applications.
Now let’s come to the main thing. How does the Verified Generate API actually work? Suppose you give a prompt—“What are Tesla’s recent delivery numbers?” A normal AI might just throw out a number. But Mira breaks that output apart. “Q4 delivered 484,000 vehicles”—this claim gets separated. Then many different models check it. Some say 97% correct, some 99%. When consensus is reached, you get the verified output + an on-chain certificate. You can audit it later if you want. It’s like a receipt. After you buy food, you can later check whether everything is correct.
In my experience, this thing works best where decisions carry a lot of weight. Imagine a fintech app. Traders are asking “Should I buy Bitcoin right now?” A regular chatbot might say “Yes, market is bullish.” But if you check with Mira, every single claim gets verified separately. “After ETF approval, price rose 18%”—this is verified. “Currently in overbought zone”—this gets flagged. So the user doesn’t blindly trust anymore; they look at the proof and then decide.
And in education too. On an education platform, students ask “How does quantum computing work?” When generated through Mira, every fact comes with proof behind it. “Qubits can exist in superposition”—98% of models agree. If there’s any wrong information, it gets caught. So students aren’t just reading—they’re knowing that what they’re reading is correct.
For developers, it’s basically a gold mine. They’ve given a Python SDK that’ssimpl simple.
One line to integrate. And you pay with $MIRA tokens. Node operators stake to secure the network and earn rewards. They can also vote in governance. Everything is decentralized, yet extremely easy to use.
Honestly, I think this is the next step for AI. Before we used to say “Trust AI.” Now we’ll say “Verify AI.” The era of hallucinations is over. Regulators are happy, companies are happy, and users are even happier.
If you’re a developer, a trader, or just curious about AI, go check out mira.network once. You’ll even get free credits to start.
Mira Network isn’t just making AI smarter—it’s making it trustworthy. And that’s exactly what we need most right now.
@Mira - Trust Layer of AI #Mira
