Let Builders Build, and Agents Cook.

Software used to be built by engineers. Not any more.

Low-code tools brought in domain teams. AI copilots brought in everyone else. And now agents are building and acting alongside humans; marketing, finance, HR and legal are all shipping the apps they used to file tickets for. The number of people (and things) building on your data has exploded, and it isn't slowing down.

And there's no single, standardized way to build, there likely never will be. Coding agents, AI models, infrastructure needs and even consumption models keep shifting. Committing to one fixed way of working is the riskiest move you can make right now.

All of that building relies on data, and AI is only as good as the data, and context underneath it. Agents don't just query data, they reason over it and take action on it. When the data is stale, ungoverned or out of reach, an agent doesn't just return a wrong answer; it takes a wrong action, and the next agent downstream compounds it.

"AI agents make decisions at digital speed. A poor decision by one AI agent gets exacerbated by each successive downstream AI agent." - Forrester, Streaming Data Platforms Wave, Q4 2025

That raises the bar for what a data foundation has to do.

The problem: your data is fragmented

Building on data means running a lot of it: streaming, transactional, analytics, search, caching, governance, compute. Assemble that from separate vendors and you've built yourself a pipeline nightmare; many contracts, many operating models, many APIs, and the cost shows up as latency, duplicated operations, governance gaps, lock-in, and weeks of integration work before anything ships.

Build it yourself using open source and the licenses are free, but the patching, scaling, incident response and upgrades are not - and every service you add and compute you deploy on multiplies the operational load.

The gap between "we have the data" and "our apps and agents can safely use it" is often where AI projects stall.

Building a foundation for AI-ready data

To build safely and for the myriad use cases that agents can operate against, data should be:

• Fresh: Batch still has its place, but the more agents act in real time, the more they need live context, not last night's snapshot.
• Fast: Low-latency at inference time. Slow AI is no AI.
• Governed: Trusted context agents can rely on, so they don't expose PII or act on data they were never allowed to touch.
• Reachable: Accessible to apps and agents in production, without costly replication or cross-network hops.
• Open: On open formats and standards, so your architecture can keep pace as models, tools and workflows change without lock-in.

Most stacks deliver two or three of these. The Aiven Data & AI Cloud delivers all five.

This is the Aiven Data & AI Cloud

Aiven brings the open-source services that teams run in production together under one managed control plane. We call this the Aiven Data & AI Cloud. Made for builders, whether that’s developers and engineers or teams of agents, it’s how the pieces we operate fit together into a unified offering:

• Core open-source data services: Apache Kafka®, PostgreSQL®, ClickHouse®, OpenSearch® and Valkey™, fully managed, upstream and unmodified.
• Aiven DataHub: The context and governance layer: catalog, lineage and trusted context across your estate, served to humans and agents through MCP.
• Aiven Runtime: A managed environment to run your AI agents and apps next to your data.
• A managed platform beneath it all: One control plane, a 99.99% uptime SLA, and enterprise security and compliance built in: ISO 27001, SOC 2 Type II, PCI DSS, HIPAA and GDPR, with encryption, private networking, RBAC, audit logs, and SSO.

It all runs with the same operating model on any cloud, AWS, Google Cloud, Azure and BYOC. And because it's all best-in-class open-source services and open standards, the tools you build with already know how to use it: coding agents like Claude or Codex build against Aiven out of the box. Apps and agents reach it through the Aiven Console or MCP, and run on it through Aiven Runtime.

Not just any "data cloud"

The Aiven Data & AI Cloud is for builders running apps and agents on live data. Four things set it apart:

• Open, not proprietary. Genuine open-source services, Postgres, Kafka, ClickHouse, OpenSearch, Valkey, no forks, on open standards and formats. The skills, tools and integrations your team already has just work, and your data and workloads stay portable.
• Operational, not just analytical. Built to run live apps and agents against production data; streaming, transactional state, search, caching and runtime, not just to query the past.
• No lock-in. Run where it makes sense for cost, latency, resilience and data residency, and keep the freedom to move. The exit is always open, so you stay by choice.
• Built for the agentic era. Governance (DataHub), agent access (MCP) and Runtime are native to the same open data layer, not bolted on afterward. Your agents get fresh, governed data and a safe place to act, without you stitching three products together to get there.

Build on Aiven

The way you build will keep changing, new agents, new models, new patterns every few months. What shouldn't change is fighting your own infrastructure to keep up. That's what the Aiven Data & AI Cloud takes off your plate: open-source services you can trust, the governance to use them safely, and somewhere to run your apps and agents right beside the data, managed for you, on any cloud, and yours to leave whenever you like.

Start building today.