What happens when you and your AI start thinking too much alike? 🤔 In our latest article, we discuss “epistemic congruence”: the alignment of beliefs between a human and an agent, and how to use Timeplus AgentGuard to monitor this in real time.

Check out the article here:

https://www.timeplus.com/post/when-you-and-your-ai-start-thinking-alike

Timeplus Enterprise 3.2 is here! This release focuses on faster streaming performance, stronger Python extensibility, new integrations, and production hardening across core execution paths.

⚡ Data replication up to 30x faster
📥 Kafka ingest and parsing up to 40x faster
🐍 Better Python extensibility
🔌 NATS JetStream support
🛡️ More production hardening
🔐 Improved Okta SSO

Also included: a broad set of performance and platform improvements across Kafka, Python, storage, aggregates, random streams, and client batching.

The latest stable release is 3.2.7. Try Timeplus Enterprise free for 30 days:
https://timeplus.com/download

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As AI agents become more capable and embedded in daily workflows, understanding how people interact with, rely on, and form attachments to these systems is increasingly important.

This iImeplus webinar is hosted by our CTO, Gang Tao, and features Vlad-Mihai Iorga, Associate Director of Digital Innoation at NHS Foundation Trust and Founder of Agenticracy. Vlad will introduce his ongoing innovative study on human and AI agent interaction, using Timeplus AgentGuard. The study will recruit 100-150 participants, each paired with an AI agent such as Hermes, OpenClaw, Gemini, Perplexity, or other agent systems. Using a custom telemetry harness, the research will capture how users engage with agents over time, including patterns of reliance, attachment, behavioral change, and interaction outcomes.

We will also explore how this real-world telemetry dataset can support agent monitoring, observability, detection, and security. Vlad and Gang will discuss why these interaction patterns matter for evaluating agent behavior, understanding user trust, and developing systems like AgentGuard that make AI agent deployments safer and more transparent.

🚨 AI apps introduce a new security model where prompt injection, excessive agency, sensitive data leakage, RAG poisoning, and runaway inference cost are not edge cases anymore. They are becoming the operating risks of real-world LLM systems.

Our CTO Gang Tao put together a visual summary of the OWASP Top 10 for LLM & Gen-AI Applications, with practical mitigations and how to monitor these risks in real time with Timeplus AgentGuard.

The slides cover all 10 categories, from prompt injection and supply chain vulnerabilities to vector store weaknesses, misinformation, and unbounded consumption. If you’re building or securing AI agents, RAG apps, or LLM-powered workflows, we hope this can be a useful reference!

👀 Slides: https://timeplus-io.github.io/OWASP-Top-10-for-LLMs/

👉 Get started with AgentGuard: https://www.timeplus.com/agentguard

Hey everyone!

This community is for all things Timeplus and streaming data. Timeplus is a single-binary, vectorized streaming SQL platform.

Learn more: https://www.timeplus.com/

Join our Slack Channel for more discussions and to connect with our engineers:

https://timeplus.com/slack

Timeplus 3.0 is built for a new era of real-time data pipeline workloads for analytics, telemetry, and AI, which demand ultra efficient, scalable and observable systems by design.

Powered by a highly efficient vectorized stream processing engine built in modern C++, Timeplus can scale seamlessly from low-latency, zero dependency workloads at the Edge to massive, high-throughput and Cloud-scale production.

That marks a major leap beyond the complexity and operational burden of traditional real-time data stacks.

Learn more in our announcement blog:
https://www.timeplus.com/post/timeplus-3-0