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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.

Aiven MCP: Build on Aiven from Your AI Agent

You've felt it. You're deep in a flow state with Claude or Cursor, building the next great thing, and then you hit the wall. Time to leave your editor, open a browser, click through a console, copy a connection string, paste it back, and pray you didn't fumble a character. The vibe is gone. What if your AI agent could just... do it? Deploy the database. Create the Kafka topic. Ship the app. All without you ever leaving the conversation. Today, that's real.

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.

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.

Building Agents that Remember: The OpenSearch Developer Tier

OpenSearch isn't just a search engine anymore. Recent releases moved it into AI infrastructure: agentic memory built in, Better Binary Quantization (BBQ) compressing vectors 32x, token-usage tracking, and a one-command Observability Stack. A stack for building practical AI applications, not just indexing. The catch is that production-sized OpenSearch clusters aren't where you want to prototype.

Get Kafka-Nated S2E5: Nobody Understands Kafka Costs

In this episode of Get Kafka-Nated, host Hugh Evans is joined by Stanislav Kozlovski, Apache Kafka committer, independent consultant, and author of 2 Minute Streaming — a newsletter with over 7,000 subscribers. After six years at Confluent, including time on the Kafka Serverless team, Stan went independent and has been writing and consulting full-time. He's one of the most recognised voices in the Kafka community, with over 50k followers across social media. In this session we go somewhere the streaming industry rarely goes honestly: Kafka costs.

A Developer's Guide to Aiven Apps

We recently announced the Limited Availability (LA) launch of Aiven Apps, which lets teams define, run, and scale production-ready, real-time applications using container and Compose-based workflows they already know. It provides a managed, stateless runtime that runs directly inside your data perimeter, letting you deploy applications alongside open-source data services like PostgreSQL and Apache Kafka.

Sustainability as opportunity: a new collaboration between Aiven and OxygenIT

Many businesses see emissions reduction as a cost sink: assigning people, maintaining compliance, the hard labor of calculating carbon signatures. That view is out of date – and a new partnership between Aiven and data provider OxygenIT demonstrates why. Our premise: your carbon footprint isn't just about understanding emissions; it's about understanding your business. Today, we're announcing a new service that helps with both.

Addressing Cold Start problem in Travel Personalization for OTAs

In the high-stakes world of Online Travel Agencies (OTAs) like Expedia, Hopper, Priceline, and Airbnb, seconds matter. A traveler searching for a "beachfront stay in Hawaii" isn't just looking for a room — they are reacting to weather changes, fluctuating flight prices, and social media trends. Traditional travel platforms often rely on stale data: yesterday's search history or last week's preferences. To truly compete, travel platforms must pivot to Real-Time Context Engineering.