Governed AI
AI governance
How we decide how much autonomy to give an agent, with what data and under which controls. It is the framework we use to design every agent.
Applied AI · Agentic AI
Useful autonomy. Explicit control.
We design agents around a specific operational decision, on Salesforce, on another platform or custom-built: with proportionate access to data, bounded actions and a clear path to people.
We do not delegate a decision the organization cannot explain.
Conceptual flow · service desk
Illustrative example- Input 01
Request received
Identify intent and level of risk.
- Agent 02
Analyzes with context
Queries authorized sources and applies defined policies.
- Resolution 03
Resolves or escalates
Records the outcome or hands off to a person.
Where we build
- On Salesforce
Agentforce and Data Cloud
When your data and processes already live in Salesforce, it is usually the most direct path and the easiest to govern.
- On other platforms
On what you already use
Agents and assistants inside your ERP, your service desk or your work tools, using the services and models your organization already contracts.
- Custom-built
Your own agents with MCP
When no platform covers the case: agents with narrow tools, orchestration and continuous evaluation, without tying you to a single model provider.
- 01 / Control
Trustworthy context
The agent receives only the data and context needed for the task.
- 02 / Control
Bounded actions
Permissions, policies and limits define what it can query or execute.
- 03 / Control
Human oversight
Sensitive decisions escalate to a person with context and traceability.
Autonomy ladder
We move up a level only when the evidence supports it.
- 1 / 4
Assists
Suggests and summarizes; the person decides and executes.
- 2 / 4
Recommends
Proposes an action along with the evidence behind it.
- 3 / 4
Acts with approval
Executes only after explicit sign-off.
- 4 / 4
Acts within limits
Executes autonomously on low-risk cases, with defined amounts and scope.
Where it usually adds value
- Customer service and support
- Sales follow-up and qualification
- Document review and extraction
- Back-office operations
- Internal knowledge lookup
- Data analysis and reporting
Downloadable resource
Autonomy ladder for AI agents
A 3-page guide with the design principle, the governance flow, the 3 controls and the 4 autonomy levels, to bring to your own internal conversations.
PDF · 3 pages · English
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