Aimbient

Aimbient is a backend platform for building and operating AI agents in environments where security, auditability, and human oversight are non-negotiable. It provides durable workflows that survive restarts, human-in-the-loop approval gates, credential isolation between agents, and complete audit trails. If you're running agents in production—especially in regulated industries—Aimbient is the infrastructure layer that makes them trustworthy.

Prototyping agents is easy. Running them in production, in a bank or hospital, is not. Agents must survive restarts and long waits for human approval. Every action must be audited and explainable for regulators. Credentials must be isolated and scoped, not scattered through code. Operations teams need dashboards and SLAs, not one-off Python scripts. Aimbient solves these infrastructure problems so you can focus on agent logic.

Aimbient runs agent logic as Temporal-based workflows that persist state across restarts, scale horizontally, and can pause indefinitely waiting for external signals. If your server crashes mid-workflow, Aimbient picks up exactly where it left off when it comes back. Workflows can wait for hours or days—for human approvals, external callbacks, or scheduled triggers—without consuming resources.

Human-in-the-loop means workflows can pause and wait for a human to approve, reject, or provide input before continuing. In Aimbient, you call an approval function in your workflow code, and execution blocks until a human responds. Responses arrive via WebSocket, webhook, or any frontend connected to the event bus. This is essential for high-stakes operations where full autonomy isn't acceptable.

No. Aimbient runs background agents that react to events, not conversational chatbots. It's also not a low-code builder—agents are written in Python with a typed SDK. And it's not a model host—LLM inference happens externally (OpenAI, Anthropic, self-hosted). Aimbient orchestrates the workflows that call those models and manages everything around them.

Secrets in Aimbient are encrypted at rest, scoped per agent, and accessed only through a controlled API with full audit logging. Each agent declares what credentials it needs in its manifest, and the platform enforces that agents cannot access credentials they haven't declared. This prevents credential sprawl and makes it easy to audit exactly which agent accessed which secret.

Yes, core Aimbient components—the runtime, SDK, registry, and event bus integration—are open source and production-capable. You can deploy it yourself and run agents in production. Commercial tiers add enhanced observability, advanced security features (SSO, fine-grained RBAC, secrets rotation), and SLA-backed support for organizations that need them.

Aimbient is built for platform engineers creating internal agent infrastructure, application developers building domain-specific agents, security and compliance teams who need provable guarantees about agent behavior, and OEM partners embedding agent capabilities into their own products. If you need agents that are auditable, controllable, and safe for regulated environments, Aimbient is for you.