Security
Can we approve this agent for sensitive resources? What files, data, network destinations, tools and credentials can it reach — and what happens when the agent asks for something outside policy?
Enterprise Agent Execution Platform
Put AI agents to work — within your organization's boundaries.
ContactLab gives Security, Platform, Compliance and business leaders one organization-controlled execution, policy and evidence layer. Start with Claude Code and OpenAI Codex in one bounded workflow. Expand to more teams and systems as integrations and customer demand are validated.
RUN clb_01J8X9…
Agent Claude Code
Resource payments/api
Execution profile pci-restricted-v3
Network 3 approved · 2 blocked
Credentials github-write · aws-readonly
Policy 12 passed · 1 review required
Artifacts 14 files changed
Review Approved
Illustrative example of a governed execution record — not a product screenshot.
Built for Security, Platform, Compliance and leaders responsible for approving AI adoption.
The problem is no longer whether people will use agents. It is how much access the organization is willing to give them.
Modern agents can read files, execute commands, call tools, use credentials and interact with company systems. Vendor-native controls are important, but enterprise adoption still fragments across agents, repositories, teams and deployment modes. Platform needs a consistent execution model. Security needs enforceable boundaries. Compliance needs evidence that survives the session.
Platform
Can we standardize execution without building a harness per agent? Define reusable execution profiles for supported agents instead of distributing one-off local configurations across teams and laptops.
Evidence
Can we reconstruct what happened later? Preserve session metadata, policy decisions, relevant execution events, artifacts, changes and reviewer outcomes for security and compliance workflows.
One control model between agents and company systems.
Execution flow, top to bottom: people and systems; supported agents; the ContactLab control layer; company systems.
People & systems
Security · Platform · Compliance · Business teams
Supported agents
Claude Code · OpenAI Codex
ContactLab
Identity · Execution profile · Resource policy · Network · Secrets · Approvals · Evidence
Company systems
Code · Data · SaaS · Internal APIs · Cloud resources
The resource changes. The control model does not.
Native agent controls are necessary. ContactLab adds the organization layer.
Claude Code and Codex already ship meaningful sandboxing, permissions and enterprise controls. ContactLab complements those controls — its role is to make the organization's execution boundary and evidence model durable across supported agent vendors and enterprise resources.
| Vendor-native control | ContactLab |
|---|---|
| Controls one vendor/product | Consistent organizational model across supported agents |
| Vendor-specific configuration | Organization-defined execution profiles |
| Vendor-specific telemetry | Normalized execution evidence |
| User/workspace policy | Team, resource and workload execution policy |
| Product-specific rollout | Central Platform/Security operating model |
Enable. Bound. Observe. Prove.
Enable
Give more teams a supported path to use capable agents against enterprise resources.
Bound
Define the files, data, network destinations, credentials, tools and runtime conditions available to the governed execution.
Observe
Surface relevant execution events, policy decisions, blocks and review requests while work is running.
Prove
Retain the structured execution context required for security review, audit and continuous improvement after the ephemeral workload ends.
Supported today
ContactLab currently focuses on Claude Code and OpenAI Codex. The platform architecture is designed so organizational policy and execution evidence do not depend on the lifecycle of a single agent vendor.
Claude CodeOpenAI Codex
Start with one workflow. Expand under one standard.
Adoption matures when the organization proves one valuable, sensitive workflow, turns its controls into a reusable standard, then expands to more teams, data and systems.
One valuable, sensitive, bounded and reversible workflow
Defined boundaries · Human review · Consistent evidence
More teams, data and systems as integrations and customer demand are validated
The workflow changes. The control standard remains.
Decisions the platform helps your organization make
Approve the first sensitive workflow
Start with Claude Code or Codex in a bounded, reversible workflow tied to resources the organization needs to protect.
Limit access to critical resources
Define which resources, credentials, tools and network destinations are available to each execution.
Standardize adoption across teams
Reuse boundaries, review points and evidence as more teams adopt supported agents.
Expand with evidence
Apply the same standard to new data and business systems only as integrations and customer demand are validated.
Start with one valuable, sensitive workflow.
The pilot starts with one team, one to three resources or systems and a clear business and security question. In six weeks, the organization gathers evidence to decide whether expansion should be approved, narrowed or redesigned.
1 team1–3 resources/systemsClaude Code and/or Codex6 weeksdefined controlsfinal expansion decision
See ContactLab at work.
During the meeting, we show a live or prepared governed execution in ContactLab's own company environment. You will see the enforced boundaries, a human review step and the evidence retained after the run.