AI agent evaluation replaces data labeling as the critical path to production deployment
As LLMs have continued to improve, there has been some discussion in the industry about the continued need for standalone data labeling tools, as LLMs are increasingly able to work with all types of data. HumanSignal, the lead commercial vendor behind the open-source Label Studio program, has a different view. Rather than seeing less demand for data labeling, the company is seeing more.
Microsoft's Fabric IQ teaches AI agents to understand business operations, not just data patterns
Semantic intelligence is a critical element of actually understanding what data means and how it can be used.
Databricks: 'PDF parsing for agentic AI is still unsolved' — new tool replaces multi-service pipelines with single function
There is a lot of enterprise data trapped in PDF documents. To be sure, gen AI tools have been able to ingest and analyze PDFs, but accuracy, time and cost have been less than ideal. New technology from Databricks could change that.
Databricks research reveals that building better AI judges isn't just a technical concern, it's a people problem
The intelligence of AI models isn't what's blocking enterprise deployments. It's the inability to define and measure quality in the first place.
Snowflake builds new intelligence that goes beyond RAG to query and aggregate thousands of documents at once
Enterprise AI has a data problem. Despite billions in investment and increasingly capable language models, most organizations still can't answer basic analytical questions about their document repositories. The culprit isn't model quality but architecture: Traditional retrieval augmented generation (RAG) systems were designed to retrieve and summarize, not analyze and aggregate across large document sets.
AI coding transforms data engineering: How dltHub's open-source Python library helps developers create data pipelines for AI in minutes
A quiet revolution is reshaping enterprise data engineering. Python developers are building production data pipelines in minutes using tools that would have required entire specialized teams just months ago.
The missing data link in enterprise AI: Why agents need streaming context, not just better prompts
Enterprise AI agents today face a fundamental timing problem: They can't easily act on critical business events because they aren't always aware of them in real-time.
GitHub's Agent HQ aims to solve enterprises' biggest AI coding problem: Too many agents, no central control
At its Universe 2025 conference, the Microsoft-owned developer platform announced Agent HQ. The new architecture transforms GitHub into a unified control plane for managing multiple AI coding agents from competitors including Anthropic, OpenAI, Google, Cognition and xAI. Rather than forcing developers into a single agent experience, the company is positioning itself as the essential orchestration layer beneath them all.
Intuit learned to build AI agents for finance the hard way: Trust lost in buckets, earned back in spoonfuls
Building AI for financial software requires a different playbook than consumer AI, and Intuit's latest QuickBooks release provides an example.
Research finds that 77% of data engineers have heavier workloads despite AI tools: Here's why and what to do about it
Data engineers should be working faster than ever. AI-powered tools promise to automate pipeline optimization, accelerate data integration and handle the repetitive grunt work that has defined the profession for decades.
World's largest open-source multimodal dataset delivers 17x training efficiency, unlocking enterprise AI that connects documents, audio and video
AI models are only as good as the data they're trained on. That data generally needs to be labeled, curated and organized before models can learn from it in an effective way.
