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Introduction to CertOps

The Mission: "Trust, But Verify"​

CertOps is the industry's first dedicated AI Quality Assurance Platform. It exists to solve the "Black Box Problem" of Generative AI in the enterprise.

The Problem​

Enterprises are building AI agents using a fragmented ecosystem:

  • Team A uses LangChain on Azure.
  • Team B uses AutoGen on AWS.
  • Team C uses raw OpenAI API calls.

There is no unified way to answer the critical question: "Is this agent safe to release?"

The CertOps Solution​

CertOps acts as the Universal Verifier. We do not build the agent. We do not host the agent. We audit the agent.

We provide the "J.D. Power" stamp of approval that allows Compliance Officers to sleep at night and Developers to deploy with confidence.

The Platform Hierarchy​

The CertOps platform provides a comprehensive suite of tools designed to thoroughly test, evaluate, and certify AI outputs before they reach your end-users.

1. Centralized "Ground Truth" Datasets​

Instead of hardcoding test cases into your deployment scripts, CertOps centralizes your Datasets within the SaaS platform. These datasets act as the immutable "ground truth" and can be dynamically mapped to any system component, supporting both raw text and complex multi-modal assets (images, PDFs) via the Media Hub.

2. The 3-Tier Quality Matrix (Metrics)​

CertOps does not rely on a single grading logic. We rigorously evaluate responses using a 3-tier matrix:

  1. Deterministic Local Gates: Fast, zero-cost rules like Regular Expressions, valid JSON extraction, or semantic Cosine Similarity.
  2. Pointwise Evaluation: Absolute benchmarking using an LLM-as-Judge to score an isolated answer against 14+ built-in criteria (e.g., Hallucination, Harmfulness, Relevance).
  3. Pairwise Regression: Side-by-side behavioral comparison. We detect "drift" by forcing a judge model to compare your new uncommitted code directly against historically approved "Production" baseline outputs.

3. Agnostic Model Configurations​

CertOps doesn't lock you into a vendor. You configure your own Model Configs and routing paths, securely injecting credentials into the engine. You can use ANY foundational model (OpenAI, Anthropic, Gemini) as your Judge, or even provide a custom base_url to utilize your own securely self-hosted, air-gapped models.

4. Configuration as Code (The Manifest)​

All of the above entities are orchestrated by the certops.yaml Manifest. You define exactly which API endpoints to target, which datasets to use, and which metrics are considered "Hard Blocking Gates vs Soft Warnings". The manifest lives directly inside your version control system alongside your application code.

5. Automated CI/CD & Hybrid Execution​

The CertOps CLI executes the manifest. It is designed to run in your CI/CD pipelines as an automated "Gatekeeper"—immediately stopping a deployment with an exit code 1 if the metrics degrade.

Furthermore, the CLI utilizes the CertOps Local Bridge, an ephemeral TLS-encrypted tunnel that allows developers to run massive regression evaluation matrices directly against their localhost development services, all without deploying any code.