Luno
Luno provides an AI agent platform, LunoOS, where autonomous agents own and complete operational work end to end across support, sales, back-office, and operations. The platform connects to existing enterprise systems, learns workflows through a living context layer, and includes a governance layer for testing and auditing agent actions. Luno reports 30-50% lower operational costs and 2-5x higher productivity for deployed operations.
- AI Agents
- Artificial Intelligence
- Enterprise Software
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Companies are constrained by manual processes, large teams, and long cycles that limit scalability and operational efficiency. Repetitive work in support, sales, back-office, and operations—such as ticket resolution, invoice reconciliation, lead follow-up, and scheduling—creates bottlenecks, backlogs, and delays that are expensive to staff and hard to scale without adding headcount.
Solution
Luno provides an AI agent platform, LunoOS, where autonomous agents own operations end to end and complete work, rather than serving as chatbots or copilots. The platform connects to existing enterprise systems, learns how a business operates through a living context layer, and deploys lead and specialized agents to execute complex, multi-step workflows. Agents handle what they can independently and escalate what genuinely requires human involvement with full context. The system includes a governance layer that defines quality standards, tests agents before deployment, and audits actions in production to ensure accountability and compliance. Luno reports 30-50% lower operational costs and 2-5x higher productivity for deployed operations.
Target Audience
Luno targets enterprise organizations across industries including retail, banking and finance, aviation, logistics, healthcare, insurance, energy, infrastructure, global trade, and agriculture, focusing on operational functions such as support, sales, back-office, and operations.
Features
- Agentic layer with lead agents that decompose complex operations into sequential steps, delegate to specialized agents, and coordinate completion
- Context layer that captures workflows, exceptions, and edge cases from every performed operation, creating a single source of truth for all agents
- Integration layer that connects to legacy systems, ERP, CRM, HRIS, document stores, and internal APIs, enabling agents to take action, not just read data
- Governance layer with definable quality standards, pre-production testing against real scenarios, sampled production audits, and human oversight interfaces
- Enterprise security with end-to-end encryption, no training on private data, IAM compliance, audit logs, and automatic failover for continuous operation
- Deployment approach includes forward-deployed engineers who build operations end to end or support the client's team, with a required discovery, design, build, test, go-live sequence and post-launch support