RAG + Structured data
RAG can't answer “how much did we sell in June”
Vectors are great for documents. For business numbers, the agent needs a modeled layer and a query, not retrieval.
Vectors are great for documents. For business numbers, the agent needs a modeled layer and a query, not retrieval.
If the question has how many, how much or since when, it's a modeled layer and a query. RAG is for documents. Mixing the two is how you get an agent that guesses with confidence.
“Our data was disjointed. With Nekt, we centralized everything in one place, and SQL queries made our work much easier.”
“We centralized all databases from various sources. Nekt immensely optimized the speed and quality of our team's deliveries.”
“I’ve stopped wasting precious time on ingestion infrastructure and pay significantly less than I did with other platforms. I have much more control over transformations, and if I need a new source, they build it quickly. That used to take me weeks, not to mention the maintenance effort. The UX/UI for connecting and managing sources is excellent, and when something fails, I know exactly where the issue is without having to dig through logs.”
“Even without a tech background, I built robust pipelines. Nekt's usability added so much value that it inspired me to switch to a Data career.”
“I stopped babysitting tools and cloud costs. Now I focus on strategy and fluid pipelines, without billing scares at the end of the month.”
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