Britney Chandler
Blogs by Britney Chandler
Your AI Agent Has Access. Should It?
AI agents can retrieve information, use tools, update systems, and initiate business processes. Each added capability makes the agent more useful, but it also raises an important question: What should the agent be allowed to access?
Enterprise Knowledge, Available Securely in Google Chat
Does the company reimburse mileage? Is a receipt required? What is the limit for a meal while traveling?
AI Agents Need Job Descriptions Too
When someone starts a new job, they need more than a company login and access to a few applications. They need to understand their responsibilities, the decisions they are authorized to make, the tools they should use, and when to involve someone else.AI agents need the same clarity.
Context Engineering: How Better Context Improves Accuracy, Reduces Hallucinations, and Controls AI Costs
The quality of generative AI answers depends on far more than the language model itself. Every response is shaped by the information provided before the model begins generating text.
The Business Value of Secure Enterprise AI Search
Secure AI search is often discussed as a technical or compliance topic. But for enterprises, authorization and data protection are not only about reducing risk. They also create business value.
Secure AI Search: Why Authorization and Data Protection Matter
Enterprise AI search is changing how employees find and use information. Instead of searching through disconnected systems, employees can ask questions, receive AI-generated answers, summarize content, and get guidance based on enterprise knowledge.
Finding Research Insights Across Large Enterprises
How AI-powered research discovery helps teams find and reuse knowledge fasterLarge enterprises create research constantly: market studies, customer insights, competitive intelligence, product research, innovation findings, and human-centered research.
Memory in Agentic AI: Why Context Matters
When we talk about agentic AI, it’s easy to focus on reasoning and tool‑calling. But there’s another ingredient that’s just as important: memory. Without it, even the smartest model can only handle one interaction at a time.
Inside the Architecture of an AI Agent
AI agents are often talked about as if everything depends on the model. But in real enterprise environments, the model is only one part of the story.
Demystifying Ontologies in Knowledge Graphs: building a semantic backbone for enterprise AI
Why enterprises need structured knowledgeAs organizations adopt AI to enhance search, summarization, and automation, they encounter a fundamental challenge: data resides in different systems and often lacks a common vocabulary.
Linking Non Indexed Documents with Instant Semantic Context
Context and ChallengeOrganizations frequently need to act on information that has just arrived, a management report before a board meeting, a contract from a partner, or a project update that requires immediate decisions.
Future-Proofing Enterprise AI with Secure and Flexible Deployment Options
Enterprise AI initiatives depend on reliable access to organizational knowledge. However, connecting information across cloud services, internal systems, and legacy infrastructure requires a product that can balance two critical priorities: security and flexibility.