01
CI integration
Run checks in GitHub, GitLab, Jenkins, Bitbucket, or custom pipelines.
Agent orchestration
Orchestrate AI coding with policy gates.
Start manual and earn autonomy. Cognium connects agent output, scanning, trust scoring, registry controls, and release policy into one governed workflow.
One score. Three outcomes.
One score. Three outcomes.
Every component gets a Trust Score from 0-100. The score determines what happens next: block, review, or deploy.
02
Policy routing
Approve, block, or escalate based on trust score and repository policy.
03
Workflow evidence
Attach audit artifacts to the same path developers already use.
Implementation
A control plane for agentic development
Use Cognium to coordinate scanners, specs, registries, and human review without forcing teams into a new development tool.
Agent agnostic
Use existing agents and editors instead of replacing them.
Progressive rollout
Start report-only, then move selected repositories to blocking gates.
Enterprise deployment
Run cloud, hybrid, or on-premise depending on source-code and compliance needs.
Built for services and platforms
Private skills and public skills need one trust layer.
Production separates the audience clearly: services teams turn expertise into reusable private skills, while platform teams keep shared ecosystems safe with trust gates and visible verification.
SVC
Services companies
Capture domain expertise as trusted, reusable skills that agents can use across client delivery, internal engineering, and regulated workflows.
- Private registry for proprietary methods, playbooks, and delivery patterns.
- Public registry access for verified skills outside your core IP.
- Trusted agents that reuse approved expertise without leaking it.
PLT
Platform companies
Protect marketplaces, partner ecosystems, and internal developer platforms from untrusted skills, tools, and generated code.
- Trust gates that score every skill before agents can use it.
- Trust badges that make verification visible to builders and customers.
- Audit trails for compliance, partner review, and ecosystem governance.
Comparison
How Cognium changes the workflow.
These pages are built for teams evaluating AI coding security, agent trust, and enterprise governance beyond basic scanner checklists.
| Current approach | Typical gap | Cognium approach |
|---|---|---|
| Basic automation | Agents create code quickly. | Agents create code inside controlled release policy. |
| Separate scanners | Security checks run without agent context. | Scanning, registry, and spec checks share one trust score. |
| Manual operations | Platform teams coordinate exceptions manually. | Policy gates route decisions consistently. |
Start manual. Earn autonomy.
Begin with humans approving every release. As your pipeline proves safe, Cognium auto-approves known patterns.