Relu offers an AI Operating System that unifies data, operational logic, and execution into a live operational model for large, high‑risk enterprises. By ingesting data from systems, documents, and external signals and encoding rules and approvals as executable workflows, the platform enables autonomous, real‑time decision making with built‑in monitoring, human‑in‑the‑loop control, and auditability.
Funding
$2.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Critical enterprises often rely on disparate data sources, manual approval processes, and fragmented operational tools, leading to delayed decisions, high latency, and increased risk in mission‑critical workflows.
Solution
Relu provides an AI Operating System that creates a unified, live operational model by ingesting data from systems, documents, and external signals. It encodes enterprise rules, policies, and approval logic into executable workflows that run in real context, enabling autonomous, real‑time decision making. An execution layer triggers actions, coordinates human‑in‑the‑loop tasks, and offers operator dashboards for monitoring and governance. By integrating data, logic, and action in a single platform, Relu reduces manual handoffs, improves response times, and ensures auditability across complex, regulated operations.
Target Audience
Primary customers are large enterprises in critical industries such as energy, manufacturing, logistics, and telecommunications that require autonomous, real‑time operation of complex, high‑risk workflows.
Features
- Schema‑as‑code and live operational graph for a trusted, continuously updated view of enterprise data
- Multi‑source document and signal ingestion with normalization and validation at scale
- Executable rules, policies, and context‑aware approvals modeled as adaptive workflows
- Exception handling and deterministic AI decisioning under continuous change
- Operator applications and dashboards for real‑time monitoring, human‑in‑the‑loop control, and AI execution governance
- End‑to‑end audit trails and verification of process execution across interconnected workflows