Systems | Development | Analytics | API | Testing

AI agents that forget their context are just expensive chatbots. The difference between intelligent agents and simple assistants comes down to memory architecture, specifically how well your system tracks relationships, maintains temporal context, and reasons over evolving information. Graph databases have moved from niche infrastructure to essential AI components, with GraphRAG implementations showing 80% improvements in agent truthfulness and significant accuracy gains over vector-only approaches.

What are we spending? Who’s using AI? Is it improving productivity? Here’s how we use Fivetran’s own AI connectors to turn fragmented AI consumption data into answers we can act on.

Agentic AI security is the set of controls that keep AI agents from accessing, changing, or sharing more than they should. It covers who an agent acts for, which data and tools it can use, which actions need approval, and how its activity is recorded and reviewed. AI agents are moving from pilots into daily operations. They read invoices, update records, answer customers, and trigger workflows across business systems.

LLM observability is the practice of collecting and analyzing data about how a language model application or AI agent behaves, including prompts, responses, tool calls, cost, speed, and errors, so teams can find problems, measure quality, and improve results. AI agents can now plan tasks, call tools, and work across business systems. That makes them powerful, and it also means a single request can involve many steps that no one sees directly.

Digital platforms move faster than ever today. In complicated systems, engineering teams upload code modifications numerous times a day. These apps are powered by distributed microservices, third-party APIs, and cloud resources. But many teams still validate speed with legacy workflows. Traditional load tests run solely static scripts against pre-planned scenarios. After the developers complete constructing the feature, they model historical traffic.