ONIRIS

Oniris helps cloud teams reduce costs and boost visibility with an AI-powered monitoring layer that explains your cloud spend in plain language — before it gets out of control.

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Inspiration

Cloud spending is skyrocketing, but few companies truly understand where their money goes. In speaking with CTOs, CFOs, and cloud engineers in Switzerland, we noticed a recurring pain: billing dashboards are too technical, alerts come too late, and cross-team alignment is missing. Oniris was born out of the desire to make cloud costs transparent, actionable, and accessible—not just for engineers, but for every decision-maker.

Working in consulting for global banking players, I’ve witnessed first-hand how cloud spending is often out of control—with significant amounts wasted on underutilized or misconfigured services. These inefficiencies not only hurt the bottom line, but also lead to unnecessary environmental impact through excessive energy consumption. Oniris was created to address both: reduce costs and promote sustainable, data-driven infrastructure.

What it does

ONIRIS is a cloud cost observability platform focused on Azure. It helps teams:

Monitor and visualize real-time cloud spend

Get plain-English summaries powered by AI

Receive alerts on cost anomalies and budget risks

Automate cross-team reporting via Slack, Email, and Webhooks

Set dynamic thresholds and track usage over time

In short: it translates raw billing data into strategic decisions.

How we built it

We focused on modularity and transparency from the start.

Frontend: Built with Vite, React, and TailwindCSS for fast, clean UI

Backend: Supabase for auth, data storage, and role control

Monitoring: Azure Cost Management APIs, with Grafana dashboards deployed via Ansible

AI Layer: LLM-powered agents summarize usage patterns and recommend optimizations

Deployment: Containerized setup, ready for cloud or on-premise hosting

Payment: Stripe as this is most common for SaaS products.

What it does

ONIRIS is a cloud cost observability platform focused on Azure. It helps teams:

Monitor and visualize real-time cloud spend

Get plain-English summaries powered by AI

Receive alerts on cost anomalies and budget risks

Automate cross-team reporting via Slack, Email, and Webhooks

Set dynamic thresholds and track usage over time

In short: it translates raw billing data into strategic decisions.

Challenges we ran into

Azure permissions and billing APIs are not friendly to new developers

Reducing noise in time-series data while keeping meaningful insights

Designing visualizations that don't overwhelm users

Balancing automation with accuracy in AI-generated alerts

Ensuring security and role-based access for sensitive cost data

Stripe connectors not working properly with Supabase/Netflify. Had to find a work around in bash on mac terminal by downloading packages with brew to make it work.

 Accomplishments that we're proud of

Deployed a full-stack MVP with real-time Azure integration

Build a full product with Dashboard and real time analysis which can be customized by clients later on

Created a usable AI layer that explains spend in natural language

Built a working Stripe integration

Added CO₂ impact monitoring to support sustainable IT

Interest from SMEs in Switzerland for early pilot runs

Flexible architecture that can expand to multi-cloud (AWS/GCP)

What we learned

Engineers and CFOs see cloud costs differently — we can bridge that gap

Natural language explanations improve decision-making across teams

The best dashboards are often the simplest

Building a “FinOps copilot” is more about clarity than complexity

What's next for ONIRIS

Rolling out with Swiss enterprise pilot partners

Expanding support to AWS and GCP

Training our AI agent on industry-specific usage patterns

Integrating with productivity tools like Notion, Excel, and Linear

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