Every engineering team adopting AI agents faces the same arc: excitement, then experimentation, then the creeping realization that nobody knows what these agents are actually doing in production. Logs are scattered across providers. Cost attribution is a spreadsheet exercise. Governance is a wiki page that nobody reads.

We built Rivano to fix this.

The Problem

Teams deploying AI agents today run into three compounding problems:

Fragmented tooling. You need one tool to route requests, another to monitor latency, a third to enforce PII policies, and a fourth to track spend. Each has its own dashboard, its own alert rules, and its own blind spots.
Governance as an afterthought. Compliance requirements — SOC 2, GDPR, internal audit trails — get bolted on after the agent is already in production. Retrofitting governance is expensive and error-prone.
No single source of truth. When an agent misbehaves, the debugging workflow involves correlating data across three or four systems. Time-to-resolution suffers, and incident post-mortems become archaeology.

What Rivano Does

Rivano is a single control plane that spans the full lifecycle of AI agent operations. It is organized around three pillars:

Build — Deploy agents through a managed proxy layer. Route traffic across providers, apply retry and fallback logic, and version your configurations declaratively. Rivano sits between your application and the LLM provider, so you get control without rewriting your stack.

Govern — Define policies that enforce guardrails in real time. Block PII from reaching external models, require human approval for high-risk actions, and maintain an immutable audit trail of every decision an agent makes. Policies are written in YAML and version-controlled alongside your code.

Observe — Trace every request from prompt to completion. See token-level cost breakdowns, latency distributions, quality scores, and error rates in a unified dashboard. Set alerts on the metrics that matter and catch regressions before users do.

These three pillars share a common data model, so a governance violation automatically shows up in your observability traces, and a cost anomaly links back to the specific agent configuration that caused it.

Getting Started

The fastest way to start is to point your LLM traffic through Rivano’s proxy layer. A single environment variable change gives you tracing, cost tracking, and basic governance out of the box.

# Replace your provider's base URL with Rivano's proxy
export OPENAI_BASE_URL="https://proxy.rivano.ai/v1"
export RIVANO_API_KEY="your-api-key"

From there, you can layer on policies, configure alerts, and invite your team — all from the Rivano dashboard.

The Community plan is free and includes up to 10,000 events per month, full tracing, and basic governance policies. No credit card required.

We are shipping new capabilities every week. Follow the blog for updates, and if you have questions, reach out through the dashboard or join the community on Discord.

Welcome to the vantage point.