Accelerate Releases. Predict Failures. Secure by Design.
As digital systems scale and software becomes mission-critical, engineering leaders face the pressure to deliver faster, with fewer bugs, and uncompromising security. Our AI-powered approach to CI/CD, DevSecOps, and QA doesn’t just patch the pipeline, it reimagines the entire lifecycle with intelligence, automation, and self-healing at its core.
Move beyond passive pipelines. Our AI-infused CI/CD stack predicts failures, optimizes tests, and ensures every release is faster, safer, and smarter.
Security shifts left and right with AI copilots that detect, triage, and even remediate vulnerabilities in real time, turning compliance into confidence.
Reinvent quality engineering with LLM-driven test generation, synthetic data bots, and autonomous agents that explore systems like real users.
| Feature | StatusNeo AI Stack | Traditional CI/CD |
|---|---|---|
| Cognitive Pipelines | Yes (LLM + RL + Signal Graphs) | No |
| Auto-Healing Pipelines | Integrated with observability + actions | No |
| Security Copilots | Pre-trained on industry attack vectors | Manual scanners |
| Release Confidence Scores | AI-generated release risk matrix | Guesswork |
| Shift-Left+Right QA | GenAI + Exploratory + Real Users | Linear QA workflows |
Code Llama, StarCoder2, and T5 SecCoder for secure-by-design code and infra reviews
Custom RL pipelines for optimizing test coverage and release frequency.
vLLM-backed copilots that adapt to your engineering patterns.
Signal Mesh Framework that blends logs, builds, PRs, test runs, and alerts into actionable ML signals.
30–50% faster deployment frequency
60% reduction in security incidents pre-prod
80% automation in test case creation and maintenance
20–30% lower QA and SecOps costs
Complete pipeline observability with AI-generated risk flags
StatusNeo has built the Agentic Workbench™, an enterprise-ready framework that integrates
We help enterprises transform CI/CD, DevSecOps, and QA with AI-driven guardrails, enabling faster releases without compromising security, reliability, or quality.
Every workflow becomes predictive, automated, and aligned to continuous delivery at scale