Performing data analytics with Luzmo becomes easier with the addition of ChatGPT. Luzmo IQ eases developers’ work by seamlessly integrating AI-advanced analytics into applications and workflows.
Luzmo is making AI analytics available in a new product called Luzmo IQ. According to the company, the new platform has a lot to offer developers. However, they experience great challenges in keeping up with the pace at which new data products are requested, and they can use some help.
Luzmo IQ should provide the necessary assistance. It promises to reduce the speed and allow developers to have AI search their data sets to answer questions. This reduces the time it takes to build a data product, as AI removes concerns about orchestration and back-end maintenance.
AI searches data
In effect, AI removes work and eliminates the need to code data. Luzmo IQ manages the creation, storage, and synchronization of vector embeddings in a ClickHouse database, which allows developers to implement RAG features more easily.
For example, in order to let a user search datasets for European customers, the developer previously had to manually label all data. AI, on the other hand, can interpret the data without the labels and identify all European countries, which are then presented to the user in a clear visualization.
The perfect answer
OpenAI’s LLMs control the assistant by default. Extensions to other LLMs are possible, Luzmo points out. What makes Luzmo IQ better than posing the dataset and asking questions directly to ChatGPT? ChatGPT sometimes dares to miss the mark when answering, whereas the data products with Luzmo IQ reason about how best to answer a question.
In addition, the workflow improves, so there is no need to switch between different apps when performing one task. Luzmo further pushes improvements in the workflow by offering an API architecture that allows Luzmo IQ to read data from other apps.
Finally, Luzmo IQ has better data security, which means not everything is transmitted integrally to OpenAI. A user query is initially forwarded to Luzmo’s query engine. The LLM interprets only aggregated query responses, and for datasets, its access is restricted to specified parts. This improves the protection of mission-critical data, but data needed to answer the query will still reach OpenAI.
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