Standard Agent Logic™· SAL for Teams
Teach your people the AI way to work — safely.
SAL for Teams helps employees turn daily work into simple, reviewable AI-assisted workflows. The front door is training. The trust layer is job data, ownership, review gates, and governance records underneath.
9,483
job and standards records
5
classification systems
SOC / CFR / NIST
standards mapped
Patent
pending
The team method
Start with adoption. Add governance where it matters.
Most AI rollouts fail because people are told to “use AI” without being shown what to do with their actual work. SAL starts with real tasks, teaches one repeatable pattern, and then turns the useful workflows into helpers teams can supervise.
Teach the method
Employees learn the same simple pattern: Task, Goal, Info, Rules, Output, Next Step.
Keep humans in charge
SAL makes the handoff clear: AI drafts, organizes, and summarizes; people review and decide.
Add guardrails
Teams can define owners, review gates, boundaries, and what must be checked before work is used.
How a workflow becomes safe
The same simple logic can scale from one employee to a whole team.
SAL does not ask people to learn a new technical language. It asks them to describe the task, goal, info, rules, output, and next step. That is easy enough for adoption and structured enough for governance.
Start with one real task from the employee's day.
Turn it into Standard Agent Logic in plain English.
Save the reusable prompt or helper for repeated work.
Attach ownership, review rules, and audit evidence when the workflow matters.
The governance model
When a helper touches important work, SAL creates the control layer around it.
The principle is simple: no important AI workflow should be ownerless, unexplained, or unreviewed. SAL maps the work, attaches ownership and review, and preserves the evidence a team can stand behind.
AI Agent
Any autonomous agent entering the enterprise
SAL Governance Layer
Classify, govern, and assign accountability
SOC · NIST · CFR Mapping
Standards mapped from the registry
Verification + Audit
Evidence, review gates, audit trail
Enterprise Deployment
Governed release into regulated work
Core controls
Classify, govern, verify, and audit the helpers doing the work.
Classify
Map work and helpers to source-backed roles instead of loose labels.
Govern
Define what the helper can do, what it cannot do, and who reviews it.
Verify
Keep a citable record of the helper, its logic, standards, and review status.
Audit
Preserve mappings, approvals, and evidence so teams can explain how AI is being used.
The SAL Governance Record
The record that makes AI work explainable.
The governance record answers the questions a manager, customer, auditor, or legal team will eventually ask: what is this helper for, who owns it, what data does it use, what rules does it follow, and what must a human review?
Review the methodologyRecord Schema
SAL Governance Record
Agent Identity
- Registered agent ID
- Operational role
- Deployment owner
Governance Metadata
- Action boundary
- Escalation path
- Policy controls
Standards Mapping
- SOC role fit
- CFR surface
- NIST control family
Evidence Package
- Source citations
- Review approvals
- Audit artifacts
Runtime Visibility
Review gate
Required before action
Audit trail
Events retained
Public verify
Record can resolve
The trust engine
Friendly coaching on top of source-backed job data.
SAL is not just a chatbot. It is a workflow coach grounded in a registry of job and standards records spanning occupations, regulations, cybersecurity, industries, and international mappings.
Explore the job librarySOC
Occupations
CFR
Federal regulations
NIST
Cybersecurity
NAICS
Industries
Make AI useful first. Make it governable next.
Teach the simple workflow method, save the helpers that matter, and add the controls your team needs before AI becomes business-critical.