venturebeat
Why Google’s File Search could displace DIY RAG stacks in the enterprise

By now, enterprises understand that retrieval augmented generation (RAG) allows applications and agents to find the best, most grounded information for queries. However, typical RAG setups could be an engineering challenge and also exhibit undesirable traits. To help solve this, Google released the File Search Tool on the Gemini API, a fully managed RAG system “that abstracts away the retrieval pipeline.” File Search removes much of the tool and application-gathering involved in setting up RAG pipelines, so engineers don’t need to stitch together things like storage solutions and embedding creators.  This tool competes directly with enterprise RAG products from OpenAI, AWS and Microsoft, which also aim to simplify RAG architecture. Google, though, claims its offering requires less [...]

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Destination
The Displace Hub can make your normal TV wireless

Displace first tried its hand at reimagining the TV in 2023, with a wireless screen that suctions onto walls and features built-in rechargeable batteries. At CES 2026, the company is not only introduc [...]

Match Score: 236.12

venturebeat
The retrieval rebuild: Why hybrid retrieval intent tripled as enterprise RAG programs hit the scale wall

Something shifted in enterprise RAG in Q1 2026. VB Pulse data spanning January through March tells a consistent story: the market stopped adding retrieval layers and started fixing the ones it already [...]

Match Score: 120.34

Destination
Displace will finally ship its wireless 4K OLED suction TVs in March of this year

We first checked out Displace TV back at CES 2023 and were pretty impressed with the company's 55-inch 4K OLED screen — it was wireless, had hot-swappable batteries and you could stick it onto [...]

Match Score: 118.06

venturebeat
Agent context layers: Enterprises governing their AI data are catching twice as many bad answers as the ones who aren't

Across 101 enterprises, the context feeding AI agents is failing often and repeatedly. Sixty-eight percent have traced a confident but wrong agent answer to missing or inconsistent business context in [...]

Match Score: 113.47

venturebeat
Enterprise AI agents are only as reliable as the messiest documents behind them

Enterprise AI has largely been built around context engineering. Teams connect enterprise systems, generate chunks and embeddings, build retrieval pipelines, and assemble the context needed by individ [...]

Match Score: 111.01

venturebeat
Google just redesigned the search box for the first time in 25 years — here’s why it matters more than you think.

For a quarter century, the Google search box has been one of the most recognizable interfaces in computing: a thin white rectangle, a blinking cursor, a few typed words, and a list of blue links. On T [...]

Match Score: 107.51

venturebeat
Nimble claims its new, domain-specialized Web Search Agents cut token costs in half while boosting retrieval accuracy

Nimble, a New York City-based tech startup VentureBeat previously covered for its efforts to re-invent web search for enterprises by using multiple AI agents to improve accuracy and depth, is taking a [...]

Match Score: 107.41

venturebeat
Databricks' Instructed Retriever beats traditional RAG data retrieval by 70% — enterprise metadata was the missing link

A core element of any data retrieval operation is the use of a component known as a retriever. Its job is to retrieve the relevant content for a given query. In the AI era, retrievers have been used a [...]

Match Score: 100.31

venturebeat
Six data shifts that will shape enterprise AI in 2026

For decades the data landscape was relatively static. Relational databases (hello, Oracle!) were the default and dominated, organizing information into familiar columns and rows.That stability eroded [...]

Match Score: 97.77