What security asks
Where are agent prompts going? What data leaves our environment? Are secrets exposed to agent runtimes? Can we prove compliance for every AI-generated change?
Harness Engineering for Enterprise AI
Your teams already use AI agents. Your governance hasn't caught up.
Claude Code and Codex CLI are running across your organization right now — engineering, marketing, operations, legal, finance. No sandbox. No egress control. No evidence trail. ContactLab moves every AI-generated action from informal usage into a governed operating model. Without changing how your people work.
govern tenant login, roles, permissions
sandbox runtime, image, skills, egress
execute Claude Code / Codex CLI
monitor live events, policy blocks
approve human review before continue
evidence artifacts, logs, audit trail
measure usage, cost, governance maturity
The problem no one planned for
AI agents are writing code, analyzing data, generating documents, and touching production systems across your organization. You can't see where, can't control what they access, can't prove what they changed. 94% of enterprises are concerned about uncontrolled AI adoption. The gap between agent usage and governance grows every day.
What platform asks
Where does agent code execute? Who approves network access? How do we standardize execution across teams? What happens when something goes wrong?
What compliance asks
Can we show an audit trail for AI-generated changes? Who approved the run? What did the agent access? Where is the evidence if regulators ask?
The shift: from prompts to systems
The industry moved through three levels of AI enablement. Most enterprises are stuck at level one or two. ContactLab operates at level three.
Prompt Engineering — craft better instructionsContext Engineering — provide the right informationHarness Engineering — build reliable systems around the model
Prompt = moment. Context = foundation. Harness = system. ContactLab is the execution layer of your Harness Engineering practice.
From sandbox to audit trail
Every agent run follows the same governed lifecycle — from access control to governance maturity. Seven steps. Zero gaps.
Govern access
Tenant-scoped login, role-based permissions, and user administration. Control who can define sandboxes, launch runs, approve actions, and review evidence. Every user operates within their assigned scope.
Define the sandbox
Configure runtime, base image, tools, skills, prompt templates, managed files, MCP connections, scoped secrets, and approved egress destinations. Every parameter is defined upfront. Nothing is left to runtime discretion.
Launch the run
Select Claude Code or Codex CLI, choose a sandbox, attach context and documents, set effort level, and trigger an ephemeral agent session. The runner exists only for the task duration. No persistent access between runs.
Monitor execution
View live run status, tool activity, runtime events, policy blocks, and token usage in real time. Cancel runaway runs. Keep execution inside predefined boundaries. Every action is captured as a structured event.
Approve when needed
Route sensitive execution steps through human approval before the agent continues. Security and platform teams control what requires review. No agent action bypasses your approval workflow.
Preserve evidence
Retain events, artifacts, logs, manifests, diffs, audit records, and review outcomes in tenant-scoped storage. Evidence survives the ephemeral runner. Reviewers see what changed, what policies applied, and who approved.
Improve governance
Track usage metrics, audit history, catalog adoption patterns, and reviewer outcomes. Measure active teams, cost signals, and governance maturity across your organization. Every cycle makes the next one stronger.
Start governed on day one
No cold-start problem. ContactLab ships with a governance catalog of pre-configured resources your teams use immediately — no custom sandbox builds, no security review backlog.
600+ platform-managed skills
Ready-to-use, one-click governed skills for every workflow. Your teams select from a curated catalog and launch governed execution immediately. No custom configuration needed. No security review per skill.
SkillsPrompt TemplatesBase ImagesEgress ProfilesMCP ConnectorsManaged Files
One-click governed execution
Teams start with platform-managed templates and policies instead of building from scratch. Security pre-approves catalog resources. Teams self-serve within governed boundaries. Adoption starts in hours, not weeks. Governance is a capability, not a bottleneck.
Every agent run is treated as untrusted
AI agents should not run casually on personal machines or unrestricted internal environments. ContactLab separates the application plane from the agent execution plane, applies network and credential boundaries, and stores only artifacts and audit-relevant output. The harness matters more than the model.
Every run produces a traceable record
SessionEventPolicy DecisionArtifact ManifestReview OutcomeAudit Record
Supported agents
Claude CodeOpenAI Codex CLI
Designed for the ecosystem
Built first for Claude Code and Codex CLI. Designed as a cross-vendor execution layer for the broader AI agent ecosystem.
Cursor CLIGemini CLIAmazon Q DeveloperWindsurfGitHub Copilot CLIDevin AIAiderCline CLIOpenHands
Prove the value in 90 days
No long commitment. Govern your first AI agent in weeks. Validate with your security and platform teams. Decide with evidence.