Heplon provides a platform that lets development teams ship AI‑generated code while maintaining system stability. It uses coding agents that automatically iterate on code to enforce platform standards, catching errors such as missing database migrations or untagged builds before they reach production. By integrating with CI/CD pipelines, Heplon ensures that only production‑ready, standards‑compliant code is delivered to engineers.
Funding
Funding not disclosed
Founders
Product
Problem
Platform engineering teams are overwhelmed by the need to keep internal developer platforms stable while supporting rapid, AI‑generated code changes. Developers frequently encounter deployment failures, missing container images, or mismatched database migrations that require manual intervention, slowing delivery and increasing operational risk.
Solution
Heplon provides AI‑driven coding agents that act as an automated platform guardrail. The agents monitor source control, CI/CD pipelines, and orchestration tools, detecting violations of platform standards such as untagged commits, incompatible database schema changes, or missing Docker images. When an issue is found, the agent suggests corrective actions—e.g., tagging a commit to trigger a build—or automatically opens a pull request to fix the problem. By integrating with developers' existing tools (e.g., Slack, Teams, Claude Code, Cursor) and platform services (GitHub/GitLab, Kubernetes, ArgoCD, PagerDuty, Backstage), Heplon ensures only production‑ready code reaches deployment, reducing manual triage and improving system reliability.
Target Audience
Heplon is aimed at platform engineering teams and site‑reliability engineers responsible for internal developer platforms, as well as the developers who consume those platforms and need automated assistance to ship code safely.
Features
- Real‑time linting of platform compliance directly from the developer’s terminal or chat interface
- Automatic detection of missing container images, untagged commits, and incompatible database migrations
- Context‑aware suggestions and one‑click fixes, such as generating git tags to trigger builds
- Auto‑generated pull requests that apply platform‑standard fixes and enforce best practices
- Deep integrations with source control, CI/CD, Kubernetes, ArgoCD, PagerDuty, and knowledge bases like Backstage and Confluence
- Continuous analysis of platform usage to surface friction points and proactively propose reliability improvements