Generative AI applications continue to heat up in the crypto industry, and many institutions try to introduce AI to enhance the research process, but often stop at the proof-of-concept (PoC) stage due to high error rates, unstable response quality, and uncontrollable costs. However, Delphi Digital is one of the few examples of successful practical products. Mira Network today officially released its latest case study, detailing how the decentralized AI infrastructure provided by Mira helped Delphi Digital launch Delphi Oracle, an intelligent assistant with caching, routing and authentication mechanisms, greatly improving the query experience for research teams and users.
Check out how we helped turn deep dives into interactive experiences at @Delphi_Digital, powering their Oracle.
Delphi Oracle 是一個個人 AI 研究伴侶，內建於報告中。我們的驗證網絡確保每個回應都是準確和可靠的。 pic.twitter.com/VzAkrvMGTi
— Mira (@Mira_Network) June 5, 2025
Three Major Pain Points of Traditional AI Assistants
Delphi Digital encountered the following difficulties when initially attempting to build its own AI assistant:
The issue of data illusion is serious, and the accuracy of the response content cannot be guaranteed.
High computational costs, the more queries, the heavier the expenses.
The system cannot be scaled to the level of real products and can only serve as an internal testing tool.
This made it impossible for the first generation prototype to go online, let alone promote it to end users.
The three solution modules provided by Mira
In 2024, Delphi decided to adopt the Mira Network architecture to restart the project. Three core technology modules have become the key turning points:
Smart Query Routing: Automatically determine the complexity of query content, handling simple questions with cache processing, and only utilizing large language models when precise inference is required.
Smart Caching System Klok: Establishes pre-generated content for high-frequency queries, significantly reducing latency and computational costs.
Decentralization verification layer: Mira nodes will validate and reach consensus on each AI response, reducing error rates and misleading risks, and enhancing overall credibility.
After the introduction, Delphi Oracle will reduce the cost of a single query by 90%, and the response time will be shortened to within 100 milliseconds, successfully meeting the online standards.
From research tool to product interface
Currently, Delphi Oracle has been integrated into the Delphi Digital official website, becoming the main entry point for members to find research reports. Common application scenarios include:
Interpret obscure passages in technical reports and quickly summarize key points;
Query historical reports and specific protocol data (such as EigenLayer, Lido);
Link past research to establish a data connection across multiple periods.
The Delphi team pointed out that Oracle is not just a tool, but has changed the way readers interact with research reports. Many old reports that were previously ignored have now become "askable, citable, and readable" through AI.
Mira Outlook: Building Usable Infrastructure for AI onchain
For Mira, the successful landing of Delphi Oracle is not only the result of technical cooperation, but also an example of product thinking. Through the authentication layer, query offload, and caching mechanism, Mira shows a feasible path for AI systems to land in on-chain scenarios. Mira will continue to expand the protocol function to support more models, multi-source data invocation and cross-chain deployment, with the goal of creating a "commercial, verifiable, and cost-saving AI layer" for developers and product teams.
This article published by Mira discusses the Delphi Oracle case study: How it helps Delphi Digital reshape the encryption research experience with AI, first appeared in Chain News ABMedia.
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Mira Releases Delphi Oracle Case Study: How to Help Delphi Digital Reinvent the Crypto Research Experience with AI
Generative AI applications continue to heat up in the crypto industry, and many institutions try to introduce AI to enhance the research process, but often stop at the proof-of-concept (PoC) stage due to high error rates, unstable response quality, and uncontrollable costs. However, Delphi Digital is one of the few examples of successful practical products. Mira Network today officially released its latest case study, detailing how the decentralized AI infrastructure provided by Mira helped Delphi Digital launch Delphi Oracle, an intelligent assistant with caching, routing and authentication mechanisms, greatly improving the query experience for research teams and users.
Check out how we helped turn deep dives into interactive experiences at @Delphi_Digital, powering their Oracle.
Delphi Oracle 是一個個人 AI 研究伴侶，內建於報告中。我們的驗證網絡確保每個回應都是準確和可靠的。 pic.twitter.com/VzAkrvMGTi
— Mira (@Mira_Network) June 5, 2025
Three Major Pain Points of Traditional AI Assistants
Delphi Digital encountered the following difficulties when initially attempting to build its own AI assistant:
The issue of data illusion is serious, and the accuracy of the response content cannot be guaranteed.
High computational costs, the more queries, the heavier the expenses.
The system cannot be scaled to the level of real products and can only serve as an internal testing tool.
This made it impossible for the first generation prototype to go online, let alone promote it to end users.
The three solution modules provided by Mira
In 2024, Delphi decided to adopt the Mira Network architecture to restart the project. Three core technology modules have become the key turning points:
Smart Query Routing: Automatically determine the complexity of query content, handling simple questions with cache processing, and only utilizing large language models when precise inference is required.
Smart Caching System Klok: Establishes pre-generated content for high-frequency queries, significantly reducing latency and computational costs.
Decentralization verification layer: Mira nodes will validate and reach consensus on each AI response, reducing error rates and misleading risks, and enhancing overall credibility.
After the introduction, Delphi Oracle will reduce the cost of a single query by 90%, and the response time will be shortened to within 100 milliseconds, successfully meeting the online standards.
From research tool to product interface
Currently, Delphi Oracle has been integrated into the Delphi Digital official website, becoming the main entry point for members to find research reports. Common application scenarios include:
Interpret obscure passages in technical reports and quickly summarize key points;
Query historical reports and specific protocol data (such as EigenLayer, Lido);
Link past research to establish a data connection across multiple periods.
The Delphi team pointed out that Oracle is not just a tool, but has changed the way readers interact with research reports. Many old reports that were previously ignored have now become "askable, citable, and readable" through AI.
Mira Outlook: Building Usable Infrastructure for AI onchain
For Mira, the successful landing of Delphi Oracle is not only the result of technical cooperation, but also an example of product thinking. Through the authentication layer, query offload, and caching mechanism, Mira shows a feasible path for AI systems to land in on-chain scenarios. Mira will continue to expand the protocol function to support more models, multi-source data invocation and cross-chain deployment, with the goal of creating a "commercial, verifiable, and cost-saving AI layer" for developers and product teams.
This article published by Mira discusses the Delphi Oracle case study: How it helps Delphi Digital reshape the encryption research experience with AI, first appeared in Chain News ABMedia.