Have you ever wondered, why should you trust the on-chain prices that cause you to get liquidated, lose bets, or see your NFTs shrink?

Many people feel reassured simply because of the concept of "decentralization." But there's an awkward truth—if the data fed into smart contracts is manipulated, then no matter how perfect the code is, it’s just an efficient money-grabbing machine.

So the question is: who guarantees that the on-chain data is real?

## The "Little Tricks" of Oracles

Currently, many oracles operate in a rather crude manner. They pick a price from a data source at random, with no way to verify the source or ensure accuracy, and then just push it onto the chain. If something goes wrong, few people will pursue accountability.

But some projects are starting to do things differently. For example, they treat on-chain data verification as a true "profession."

## The "Three Barriers" Before Data Enters the Chain

First, multi-source data collection. The price of a coin isn’t just fetched from a single exchange. Instead, data is simultaneously gathered from mainstream exchanges, media price sources, and on-chain liquidity pools, then compared. If there’s a big discrepancy, it’s flagged as suspicious.

Second, AI anomaly detection. Machine learning models run to scan for abnormal price behaviors. Sudden surges on a small exchange? Price fluctuations beyond normal ranges? The system automatically flags these and sends them back for re-verification. This isn’t manual review—it's real-time automatic filtering.

Third, distributed node voting. Validation nodes around the world stake tokens and reach consensus on the cleaned data. No single node decides; instead, over half the nodes must agree before the data is committed to the chain. The benefit is that if a node attempts to cheat, others will expose it publicly, and the cheating node will have to pay the price.

This process is like importing food inspection—it's not just about sticking a label and selling; it involves nucleic acid testing, pesticide residue checks, and smuggling inspections, ensuring each batch is trustworthy.

## On-Chain and Off-Chain "Double Play" Design

Interestingly, this system isn’t purely on-chain. Off-chain, there’s an AI processing pipeline: converting various unstructured data (contracts, news, social media, even videos) into structured formats that the chain can understand. This allows real-world information changes to be reflected on-chain more quickly.

The on-chain part is responsible for final consensus and recording. The combination of these two layers ensures data integrity without overburdening on-chain nodes.

## Why Is This Important?

You might ask, isn’t it just data verification? Why make it so complicated?

Indeed, it is. Because now, DeFi contracts have reached the scale of billions of dollars. Fake data could lead to tens of millions in liquidations. In derivatives markets, even a delay of a few seconds in price feeds can be exploited by arbitrageurs to siphon off profits.

In the NFT market, a false floor price can directly cause the entire project’s confidence to collapse. So, data accuracy has upgraded from "nice to have" to "must have."

## In Conclusion

Transparency on the blockchain is a key selling point of Web3, but transparency depends on the data being truthful. Otherwise, it’s like a "glass house of scammers"—you see clearly, but everything you see is fake.

Projects building the infrastructure for data verification behind the scenes may not be as glamorous as exchanges, but what they do might be more critical than anyone. Without them, the entire on-chain world has no foundation.