Control is what makes autonomy possible.
Enable AI agents to complete real enterprise work within clearly defined permissions, policies, data boundaries, and human approval requirements.
CBOT embeds governance into the complete AI lifecycle, from agent design and model access to runtime execution, production changes, and operational review. Define the boundaries. Authorize the action. Trace the outcome.
“Change the customer's payment plan.”
- Identity verified
- Agent permission confirmed
- Customer data access approved
- Approved model selected
- Business rules validated
- Human approval required
The more AI can do, the more clearly its boundaries must be defined.
Earlier AI systems mainly answered questions. Enterprise AI agents can now access sensitive information, use tools, update systems, initiate workflows, and influence business outcomes. This creates significant value, but also introduces operational, regulatory, data, and accountability risks. Governance keeps AI autonomy aligned with enterprise policy.
- Which agent can access this information?
- Which model is approved for this workload?
- Can the agent only read the system, or can it update it?
- Is the action within the approved business process?
- Does the decision require human approval?
- Can the complete interaction be reviewed later?
Governance is not a barrier to enterprise AI. It is the foundation for production AI.
BUILT FROM REGULATED ENTERPRISE EXPERIENCE
Designed where control is not optional.
CBOT has developed and operated enterprise AI across banking, financial services, insurance, public-sector environments, telecom, and other large organizations. In these environments, authorization, data protection, auditability, operational continuity, and human accountability are fundamental, and that experience shapes how CBOT designs AI agents and workflows. Use autonomy where it creates value; preserve control where it matters.
General product question
A non-sensitive request the agent can answer directly from approved knowledge.
GOVERNANCE APPLIED
Use autonomy where it creates value. Preserve control where it matters.
GOVERNANCE CONTROL PLANE
One control plane across every AI agent.
CBOT governs the models, knowledge, systems, actions, and human decisions used throughout an AI workflow. Each agent receives only the access and autonomy required to complete its role. Select a layer to see the controls it defines.
Identity & permissions
Define who can access the platform; which teams can design, review, approve, or publish; which roles can inspect conversations and operational data; and which agent can use which system or tool, with role-based access, SSO, MFA, and enterprise identity integration.
Every agent receives the minimum authority required to complete its role.
Every action follows an approved path.
CBOT combines language models with enterprise knowledge, deterministic logic, workflow rules, output validation, confidence thresholds, and human oversight. The purpose is not to eliminate every possible AI risk, it is to ensure AI-generated outputs do not become enterprise actions without the required controls.
- 01
Understand
The AI agent interprets the user's request.
- 02
Ground
The response is supported with approved enterprise knowledge and context.
- 03
Validate
The output is checked against expected format, structured data, business rules, and workflow conditions.
- 04
Authorize
Permissions and approval requirements are evaluated.
- 05
Execute or escalate
The action is completed, sent for human approval, transferred to a human team, or blocked.
- 06
Record
The interaction and available execution details are stored for review.
Not uncontrolled autonomy. Enterprise-controlled execution.
Keep people in control of the decisions and changes that matter.
Human oversight should be part of the AI workflow, not an emergency process outside it. The same applies to production changes: prompts, workflows, models, integrations, and agent permissions should not change without authorization, version control, and the ability to reverse the change.
HUMAN CONTROL
- Review sensitive decisions
- Approve high-impact actions
- Handle policy exceptions
- Take over low-confidence interactions
- Inspect failed or escalated conversations
- Add feedback and corrections
RUNTIME APPROVAL
- AI recommendation
- Human approval
- Action executed
CHANGE CONTROL
- Role-based editing & publishing permissions
- Approval workflows
- Version history
- Version comparison
- Controlled release
- Rollback to a previous approved version
PRODUCTION APPROVAL
- Draft change
- Review
- Approved version
- Production
- Rollback available
Every sensitive action requires accountability. Every production change requires control.
Control where data goes. Preserve the evidence of what happened.
AI interactions may contain customer messages, voice recordings, prompts, documents, enterprise knowledge, model responses, and system actions. CBOT lets organizations control where this information is processed, who can access it, how long it is retained, and how critical activity is reviewed.
DATA CONTROL
- SaaS, private-cloud, hybrid, and on-premise deployment
- Configurable retention
- Anonymization and deletion
- Encrypted storage and transmission
- Controlled model and endpoint access
- Customer-defined data boundaries
TRACEABILITY
- Conversation transcript
- Input prompt
- Selected model
- Model response
- Latency and token usage
- Fallback activity
- Confidence and escalation information
- Tool or system action
- User and approval activity
- Version and release history
Governance requires both control and evidence.
Frequently asked questions
What is enterprise AI governance?
Enterprise AI governance is the set of policies, permissions, controls, responsibilities, and review processes that determine how AI systems access data, use models, make decisions, execute actions, and change over time.
Why is AI governance important?
AI agents can access sensitive information, use tools, update systems, and execute business processes. Governance ensures these capabilities remain within approved enterprise, security, data, and operational boundaries.
How does CBOT govern AI agents?
CBOT combines role-based access, model and knowledge permissions, tool restrictions, workflow rules, validation steps, confidence thresholds, human approvals, version control, and auditability.
Can an agent be restricted to read-only system access?
Yes. Read and write permissions can be separated according to the agent role and workflow requirements.
Can sensitive actions require human approval?
Yes. Financial, contractual, legal, exceptional, or other high-impact actions can be designed to require authorized human approval.
Can organizations control which models agents use?
Yes. Model usage can be restricted according to workload, data sensitivity, security, language, infrastructure, and enterprise policy.
Does CBOT support versioning and rollback?
Yes. Prompts, workflows, NLU models, integrations, and agent configurations can be version-controlled and returned to a previous approved version when required.
Can model and agent activity be traced?
Available operational records can include prompts, selected models, model responses, latency, token usage, fallback activity, conversation details, escalations, system actions, and version history.
Can AI data remain on-premise?
Yes. CBOT supports fully on-premise operation of model inference, speech services, RAG, vector storage, platform runtime, analytics, and operational records.
Does CBOT eliminate all hallucinations and AI risk?
No enterprise AI platform can guarantee the elimination of every incorrect or unsupported model output. CBOT helps organizations reduce and manage risk through grounded knowledge, defined boundaries, deterministic validation, confidence thresholds, controlled actions, supervisor workflows, and human review.
Is CBOT designed for regulated industries?
CBOT is designed with the requirements of regulated and large-enterprise environments in mind, including private deployment, access control, human accountability, auditability, change management, and data governance. Final compliance depends on the organization, use case, configuration, data, deployment, and applicable regulation.
CONTROL THAT ENABLES AUTONOMY
Give AI the authority to act, without giving up enterprise control.
See how CBOT helps regulated enterprises define AI boundaries, govern access and actions, preserve human accountability, protect data, and maintain operational traceability.