C2O AI Engine
(100% Proprietary Standard)

AWS Azure GCP OCI

Our proprietary learning model processes millions of infrastructure data points, powering both Cloud FinOps and AI FinOps. We do NOT use Open Source wrappers or public LLMs. We have architected our own deterministic C2O Engine from the ground up for maximum privacy, mathematical precision, and multi-cloud normalization.

c2o-proprietary-engine-logs
Stage 1

Ingestion

Secure, read-only API polling collects millions of metadata points and CUR files without installing any agents.
Stage 2

Normalization

AWS, Azure, GCP, and OCI billing schemas are translated into a single, unified multi-cloud data model.
Stage 3

Analysis

Time-series analysis correlates cost with deep telemetry (CPU, RAM, IOPS) to establish baseline usage.
Stage 4

Recommendation

Proprietary algorithms generate mathematically proven rightsizing paths with zero performance degradation.
Stage 5

Remediation

Automated workflows execute changes via Terraform/CloudFormation or direct API calls with 1-click approval.

Proprietary Architecture

Security by Design. Zero Knowledge Processing.

The C2O AI Engine is built on a modular, microservices-based architecture designed for extreme scale and absolute security. It ingests metadata via secure, read-only APIs from AWS Cost Explorer, Azure Cost Management, Google Cloud Billing, and OCI Usage API.

Data is normalized into a unified schema, allowing our Cross-Cloud Learning Models to identify patterns that single-cloud tools completely miss. Because we own the entire AI stack, your financial data is never sent to third-party LLMs or open-source wrappers.

The Zero Knowledge PrincipleWe only process metadata (tags, resource IDs, billing lines). We have zero access to your application data, databases, or proprietary source code.

  • No Agent Installation Required (eBPF optional)
  • Strict Read-Only IAM Policies (AWS/Azure/GCP)
  • Ephemeral Data Processing Pipelines
  • 100% Proprietary AI (No External APIs)