Hey everyone, happy weekend! Today I went camping with good friends. The division of tasks was very clear: I was responsible for preparing the food, and she handled the camping gear.

Before leaving, she even specifically reminded me to bring a few buckets of instant noodles, saying they could be quickly prepared when hungry. But when we arrived at the site, we realized her small kettle was way too mini. It took nearly forty minutes to boil water, and we couldn’t stop laughing.

But today, besides sharing a little camping story, I also want to continue the previous topic about education apps and daily chat tools, and talk about a more professional field—cryptocurrency research. The requirements for AI here are much higher than what we usually use.

Take Delphi Digital, for example. They specialize in crypto research for institutions and have developed an AI assistant called Delphi Oracle.

Their clients are all institutional, so the answers must be professional and accurate—no mistakes allowed. On the other hand, their daily query volume isn’t small. If they used top-tier large models for all questions, the costs would be unsustainable. Balancing these two needs is quite challenging.

But I think their collaboration with @miranetwork offers a pretty clever solution that fully addresses this problem. First is "Intelligent Routing": for simple questions like checking cryptocurrency prices, it directly connects to market data APIs without involving the large model. Only when deep analysis is needed does it activate the full AI processing, making responses faster and saving a lot of money.

Then there's "Intelligent Caching": answers to frequently asked questions are pre-generated using high-end models and stored. When asked again, they’re retrieved directly. Less common questions are handled by cost-effective models, and the system adjusts based on user query popularity.

What I find most clever is their "Blind Test Model Selection." They created a crypto question bank, had different models answer, and then experts graded the answers without knowing which model responded. Surprisingly, some smaller models performed almost as well as expensive large models on certain questions.

They then use a mechanism similar to "selecting the most cost-effective" model—choosing the one that meets quality standards at the lowest cost for each question. This reduced costs by 90% without sacrificing quality.

This made me realize that in professional fields, AI isn’t necessarily better the more expensive it is—what matters is finding the right approach. Mira doesn’t just provide a simple model interface; they tailor a complete solution based on Delphi’s specific needs—routing, caching, and model selection—step by step optimizing the process.

Whether it’s developing education apps, daily chat tools, or professional research assistants, developers mainly look at one thing: can it solve real problems—save time, reduce costs, or ensure quality?

Mira happens to do all these well and is willing to work with teams to customize solutions. They don’t do one-size-fits-all, which is why so many developers choose them. Truly reliable!

And just a quick reminder: @BeldexCoin will end on the 31st of this month. Hurry up and make your move!!!