Jeongho Park, engineer at GraphAI and second author; Donghyoung Han, CTO of GraphAI and third author; Geonho Lee ...

One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination" — the generation of ...

Use these official MCP servers to interact with the leading database platforms via natural language through your LLM-assisted ...

DataHub's Context Intelligence mines validated SQL query history to build a semantic index for AI agents. At Miro, agents hit a 65% error rate without it.

In the split second it takes for a card payment to clear, a fintech database may execute thousands of database operations supporting payment authorization, fraud checks, and balance updates. In ...

Large language models (LLMs) have fundamentally changed what it means to be found online. These systems do not read content the way a person does, nor do they rank pages the way traditional search ...

Medical free texts such as pathology reports contain valuable clinical data but are challenging to structure at scale. Traditional natural language processing approaches require extensive annotated ...

Abstract: The Text-to-SQL task is to convert natural language queries into Structured Query Language (SQL) to achieve a natural language interface for database queries. The current research on Text-to ...

Snowflake has thousands of enterprise customers who use the company's data and AI technologies. Though many issues with generative AI are solved, there is still lots of room for improvement. Two such ...

When you're writing code, you're laying out instructions on what you'd like to see on the app you're building or the website you're designing. But there are a number of coding languages to choose from ...

At its Cloud Next conference, Google is showing off a new AI engine for AlloyDB that enables developers to embed natural language questions in SQL queries. Google is enhancing AlloyDB, its fully ...