While many people are racing to depend on a single, more powerful AI model, one problem still remains:
没有人能够保证完全消除幻觉现象。
At AINNA, we choose a different approach.
Instead of forcing one AI model to handle everything, we combine:
AINNA智能体 + MySQL + Redis + DuckDB
Each component does what it does best.
AINNA智能体 - reasoning, orchestration and decision flow
MySQL - trusted transactional data
Redis - speed, cache and workflow state
DuckDB - fast financial analytics and large-scale computation
Our principle is simple:
Use AI only when intelligence is required.
For stored facts, use databases.
For calculations, use deterministic computation.
For speed, use specialised infrastructure.
For reasoning, use AI.
This reduces unnecessary dependence on AI, lowers token usage, improves performance and limits the areas where hallucination can affect the 系统.
We are not trying to build a 财务 系统 powered entirely by the strongest AI model.
We are building a 系统 where AI is only one specialised layer inside a controlled architecture.
Because in 财务:
More AI does not automatically mean more reliability.
Sometimes, the smarter approach is knowing when not to use AI.
#AINNA #AI架构 #金融科技 #财务自动化 #MySQL #Redis #DuckDB #Artificial智能 #AI基础设施 #NeuralOps
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视觉和结构让AINNA智能体 + mysql + redis的概念更容易掌握。
看第二遍才注意到use specialised infrastructure的细节。
我特别喜欢use databases这一部分，内容没有把实施过程说得太简单。
文章把fast financial analytics and large-scale和日常运营联系起来，这一点很有帮助。
同意作者对trusted transactional data redis的判断，方向很清楚。