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A simple explanation of what a data agent is and how it works The post What Is a Data Agent? appeared first on Towards Data Science.
While the market races to add AI agents, Traction Complete is unveiling Data Agents that steward and improve the data layer every business, agent, and decision relies on. Traction...
If data gravity was the most important force in the Decade of Data, agent gravity will be the same in the Decade of Agents. Agents are wonderfully powerful technologies & they...
The modern software development landscape isn’t happening just on one surface — it’s happening across an entire ecosystem of agentic tools. Agents are being developed at an unprece...
The rise of AI agents is fundamentally disrupting applications and analytical systems. Generic AI platforms don't usually have access to the context stored within enterprise databa...
A Customer Asks One Simple Question Imagine an electricity distributor. A prolonged outage hits a neighbourhood, and under the rules a customer may be owed a Guaranteed Service Lev...
As a founding partner to the new Agentic Resource Discovery specification, Salesforce is helping shape the open standard that gives AI agents a universal way to find, trust, and in...
Snowflake's Data-Model-Agent framework secures the agentic enterprise with prompt injection defense, zero-copy governance and auditable agent identity.
<p class="wp-block-paragraph">Enterprise AI teams are learning a hard lesson: agents do not behave like human users.</p> <p class="wp-block-paragraph&...
A product page is not a contract. It is a presentation surface. That distinction matters more once AI agents start interacting with commerce systems. Traditional ecommerce platf...
Explore why AI agents for marketing need governed context, open ecosystems and trusted data foundations to deliver relevant customer experiences.
Until now, most organizations have treated artificial intelligence as an extension of individual productivity: a copilot capable of drafting content, summarizing information, analy...
LLM-powered agents are gaining popularity and 2026 is set to be the year of agents just like 2025. Generative AI applications have now moved from normal chatbot applications, searc...
A minimal OpenAI Agents SDK implementation where retrieval becomes a search-read-decide loop The post Agentic RAG: Let the Agent Search appeared first on Towards Data Science.
The transition from "Chatbots" to "Autonomous Agents" represents the most significant shift in enterprise software architecture since the move to the cloud. However, as we grant AI...
AI agents are moving through enterprise environments, inheriting permissions, traversing systems, and executing decisions at machine speed with minimal oversight. The identity infr...
Most teams connecting AI agents to their data warehouse start with text-to-SQL. The agent generates SQL from natural language, runs it against the warehouse, and returns results. I...
AI agents are starting to do more than recommend products. They complete the purchase. Agentic commerce is the model where a shopping agent finds, compares, and buys on a customer'...
If you've spent the last few years building data pipelines, you know the drill: ingest, transform, load. Maybe some orchestration on top. Solid work — the kind that keeps dashboa...
New platform gives enterprises a single control plane and governed runtime to manage agent sprawl, risk and AI spend Thoughtworks, a global technology consultancy that integrates d...
Stop shipping the same AI-generated UI If you use Cursor, Claude Code, Codex, v0, Bolt, or Lovable, you've seen it: Inter everywhere purple-to-indigo gradients generic "hero +...
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At the Milken Conference in May 2026, Robert F. Smith, founder and CEO of Vista Equity Partners, described a shift that every security leader should hear. Software, he said, has mo...
Most data teams have already made two decisions, even if they haven't written them down yet. The first is that Apache Iceberg will be the table format their analytical data lives i...
Agentic AI is moving fast. Enterprises are shifting from experimentation to real deployments — using AI agents to act, not just answer. This should put integration at the forefront...
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