Olbrain is one platform that builds, runs, and governs your AI agent systems. The lead orchestrator directs the specialists and does the building. You run and govern them in plain language. Every agent runs as a self-identity, with every action captured in an immutable audit log.
Olbrain gives you the lead orchestrator — an AI agent that does the building. You describe the goal in natural language; the orchestrator directs the work through discovery, build, and deployment, and your engineers focus on review and the hard edge cases. You then run and govern them in plain language — operating the whole enterprise through one platform.
Olbrain’s north star is compose-and-integrate — build, buy, partner, or integrate, all through one orchestration layer.
The orchestrator directs a team 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. You then run and govern them in plain language: support runs across every agent, and any action can be replayed and issued as 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 self-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 ₹2 per AI message, workflow usage is ₹1 per step, and research reports are from ₹5,000 each; language-model costs are included, not passed through. Monthly, no lock-in, no minimum. Contact us to start.