Centralized AI routing has strengthened data security and simplified multi-model workflowsThe best features LLM Gateway offers include multi-provider AI access and the ability to access around 200 plus models available in the market. We just need to pass our key and set up this one, and it can access all the available models. Apart from this, it automatically routes the request based on context if we set it in LLM Gateway. Another feature is the automatic failover functionality where if something goes wrong, it redirects the request to another model. LLM Gateway also provides usage analytics with a dashboard where we can check the current usage of each model and see how many requests are going to each model. It persists data for around 30 days, so we can review usage over the last month. LLM Gateway can be self-hosted as well, which is beneficial for large companies with security concerns. I find multi-provider access and failover to be the most valuable features day-to-day. Multi-provider access integrates all available models, acting as a router between the application and LLM Gateway. If my application is using four different models, I only need to call LLM Gateway, which manages everything. We also do not need to share sensitive API keys, as the developer can directly call LLM Gateway, which handles everything seamlessly. The failover feature automatically redirects requests if something goes wrong in one model, and it is incredibly easy to configure. It does not take more than a minute to set up. One positive impact of LLM Gateway on my organization is reducing security risk. If we give API keys to everyone, they can misuse them outside the organization. However, we no longer share API keys, as users just need to call our LLM Gateway, and the API keys remain secret and contained within our on-premises setup. Security-wise, it has significantly reduced our organization's risk.
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