Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results.

Most advanced RAG systems operate within the 75% to 92% accuracy range, which may be acceptable for consumer applications but remains unacceptable for institutional finance. Henon's zero-error RAG has ...

AI was to be a miracle for businesses & consumers alike. AI implementations that were supposed to transform business ...

Explore how AI is transforming risk management in banking, enhancing credit assessments and compliance automation, while ...

As for the AI bubble, it is coming up for conversation because it is now having a material effect on the economy at large.

TORONTO, Jan. 7, 2026 /PRNewswire/ - MUFG Bank (Headquarters: Chiyoda-ku, Tokyo; President and CEO: Junichi Hanzawa; hereinafter, "the Bank") has officially adopted the data anonymization solution ...

OpenAI continues its push into healthcare with the launch of ChatGPT Health, a new feature that connects its artificial ...

Investors in alternative assets like private equity, private capital and venture capital often lock their money in for years, ...

Data sprawl has forced organizations to invest in more data security resources, and is drastically inflating data backup ...

Google Cloud’s lead engineer for databases discusses the challenges of integrating databases and LLMs, the tools needed to ...