Google’s Lang Extract uses prompts with Gemini or GPT, works locally or in the cloud, and helps you ship reliable, traceable data faster.

Enterprises face key challenges in harnessing unstructured data so they can make the most of their investments in AI, but several vendors are addressing these challenges.

Data without context is fragmented — it cannot be used to effectively train AI agents or set up an appropriate workflow for addressing customer queries.

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. In ...

As GenAI usage increases in the corporate world, many executives will likely have to answer this question from their boards: “What’s the ROI on GenAI?” ...

The jury’s out on screen scraping versus official APIs. And the truth is, any AI agent worth its salt will likely need a ...

Roughly 80% of enterprise data sits in emails, contracts, call transcripts, and PDFs where traditional databases can't touch it. Much of this "unstructured" data isn't ignored because it lacks value, ...

Jordanian authorities used an Israeli-made digital forensics system to extract personal information from mobile phones of ...

Despite the global burden of HIV-1, the majority of sequence data and research remain disproportionately focused on subtype B, primarily circulating in the global north. Sub-Saharan Africa, the ...