Novlabs offers an AI Systems Engineering platform called Clanker Cloud that automates infrastructure and application tasks through open‑source CLI agents. The cloud‑native orchestration engine provides self‑healing loops, AI‑driven resource optimization, and integrates with CI/CD and observability tools, enabling platform engineering and SRE teams to manage distributed AI‑augmented systems with reduced manual effort and cost.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises building distributed, AI‑augmented applications struggle to translate cutting‑edge AI research into reliable, production‑grade engineering. The lack of deterministic tooling for orchestrating agentic workflows leads to operational complexity, high maintenance overhead, and unpredictable system performance.
Solution
Novlabs delivers a pragmatic AI Systems Engineering platform that bridges this gap. Their Clanker Cloud service leverages the open‑source Clanker CLI agent framework to automate routine infrastructure and application tasks, enabling self‑healing, continuous optimization, and rapid iteration. By abstracting low‑level orchestration into reusable agents, engineers can focus on high‑level intent while the platform handles dependency resolution, resource allocation, and fault remediation. All operations run in a cloud‑native environment with secure, encrypted communication and full auditability, reducing manual effort and operational cost. The solution integrates with existing CI/CD pipelines and observability stacks, providing a unified view of system health and AI‑driven recommendations.
Target Audience
The primary customers are platform engineering teams, DevOps engineers, and Site Reliability Engineers responsible for large‑scale, AI‑enhanced distributed systems in enterprise or SaaS environments.
Features
- Open‑source Clanker CLI agents that encode common DevOps and SRE actions as reusable, composable modules
- Cloud‑native orchestration engine that schedules and executes agent workflows across heterogeneous environments (Kubernetes, VMs, serverless)
- Automated self‑healing loops that detect anomalies, trigger corrective agents, and log remediation steps for compliance
- Real‑time resource optimization using AI models to balance CPU, GPU, and memory utilization while minimizing cost
- Native integrations with CI/CD tools (GitHub Actions, Jenkins) and observability platforms (Prometheus, Grafana) for end‑to‑end visibility
- Secure, end‑to‑end encrypted communication between agents and the Clanker Cloud control plane, with role‑based access controls
- Extensible plugin architecture allowing custom agents to be added without modifying the core platform
- Comprehensive dashboard exposing workflow status, performance metrics, and AI‑generated improvement suggestions