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Context is King #5 - Building Safe AI Agents

As AI agents gain more autonomy, safety can't be an afterthought. In this talk from Context is King in London, Jonatan von Martens (AI Safety Engineer at ElevenLabs) shares what it actually takes to build agents that behave reliably in production. Context is King is a meetup series co-organized by Flow AI and Aiven for engineers shipping AI agents in production. No pitches — just real implementation stories.

Generate Synthetic Time Series Data in InfluxDB 3

Getting InfluxDB 3 up and running is a pretty lightweight process with the installation script. Getting time series data into it is the next step, and for exploration, basic testing, or scenarios where you don’t have a stream of time series data ready to write, that can be a point of friction. That hurdle is particularly high when you want to test the rest of the system around the data you’d be writing.

Context is King #5 - Ontologies as Executable Context for AI Agents

Can a knowledge graph do more than store facts — can it actually run your agent? In this talk from Context is King in London, Teodoro Baldazzi (Principal AI Engineer at Prometheux) makes the case for ontologies as executable context: structured knowledge that doesn't just inform AI agents, but actively shapes how they reason and act. Context is King is a meetup series co-organized by Flow AI and Aiven for engineers shipping AI agents in production. No pitches — just real implementation stories.

Context is King #5 - A Semantic Layer for the Agentic Era

Agents are only as good as the queries they can run. In this talk from Context is King in London, Egor Kraev (Co-Founder & CTO of Motley) breaks down how a well-designed semantic layer becomes the connective tissue between natural language intent and reliable data retrieval. Context is King is a meetup series co-organized by Flow AI and Aiven for engineers shipping AI agents in production. No pitches — just real implementation stories.

Satellite Telemetry, ITAR, and Data Residency: Building Architecture for Speed and Control

Satellite mission operators depend on telemetry to understand spacecraft health, ground system performance, and mission status in real-time. Operation signals help teams identify risks, investigate anomalies, and keep operations moving. When a spacecraft enters safe mode or signal strength drops during a contact window, teams need trusted telemetry immediately. But mission data moves quickly across operational systems, and every handoff makes it harder to control.

Building a Predictive Maintenance Plugin with the InfluxDB 3 Processing Engine

Predictive maintenance is one of the most compelling use cases for time series data. Instead of waiting for equipment to fail or servicing it on a fixed calendar regardless of condition, you watch the live sensor data and act when it indicates that a failure is coming. That “watch the data and act” loop is exactly what the InfluxDB 3 Processing Engine was built for.

Index your Valkey Cache and Start Searching

Aiven for Valkey includes the Valkey Search module setup and ready to go. Here's what that looks like in practice: a small online shop adding real search on top of the cache it's already running. Needle & Yarn sells the yarn you crochet with (skeins) and the design patterns you crochet from. Like a lot of e-commerce backends, it already runs Valkey as a product cache, with each product stored as a Hash for hot-path performance.

A Practical Guide to Deploying LMM-Powered Apps with CLIP and pgvector

In this article we’ll show how we built an image search demo in Aiven Apps. The demo uses the CLIP Large Multimodal Model (LMM) to turn a user’s text prompts into a vector that can be compared with the precomputed vectors for a corpus of images, allowing the user to find images based on their text. While in this example the LMM input (the text prompt) is coming from the user, the principle is the same as for an internally generated query.