Olbrain is two surfaces. Olbrain Studio is where your AI agent fleet gets built — Alchemist, an AI agent inside Studio, directs the specialists and does the building. The fleet then runs and is governed in Noesis, the operating system for enterprise AI agents — which you command in plain language. Every agent runs as a persistent, governable identity, with every action captured in an immutable audit log.
Olbrain gives you Alchemist — the AI agent inside Studio that does the building. You describe the goal in natural language; Alchemist directs the work through discovery, build, and deployment, and your engineers focus on review and the hard edge cases. The fleet then runs and is governed in Noesis, the Agent OS — you operate the whole enterprise by talking to it.
Olbrain’s north star is compose-and-integrate — build, buy, partner, or integrate, all through one orchestration layer.
See use cases for what teams build today.
Inside Studio, Alchemist directs a fleet of specialist sub-agents to discover the workflow worth automating and produce a requirements document, then build the agent and its workflow pipelines and deploy it. The fleet then runs and is governed in Noesis: Nexus handles support across the fleet, and Lumen replays any action and generates an audit packet on demand. The deeper architecture is documented in the concepts.
Instructions and purpose, knowledge, tools, connectors, workflows, and triggers — assembled for you and bound to a clear purpose at creation. Underneath, the Agency Protocol gives each agent a persistent, governable identity, so its decisions are attributable and the enterprise can answer for them. Every action lands in an immutable, append-only audit log with a signed, PII-free receipt, and PII is tokenized before it ever reaches a model. Olbrain is model-agnostic — it calls leading language models directly and swaps them freely — and owns its entire stack, including its own orchestration layer. Full detail on the capabilities page.
Olbrain customer data is stored and processed in India (Google Cloud, Mumbai). The platform is DPDP-aligned and built for RBI data residency, with tenant isolation, per-tenant key management, and role-based access control. Customer data is never used to train models. Security posture and certification status (SOC 2, ISO 27001 in progress) are kept honestly status-labelled on the Trust page.
Per-agent subscription includes build, hosting, platform updates, and support; conversational usage is ₹1 per CS-packet and workflow usage is ₹1 per step; language-model costs pass through at cost. Monthly, no lock-in, no minimum. See pricing, or open Studio to start.