Currently in early development
Your automation
succeeded. Did the outcome?
Trustiform is being built to verify that agents and automations actually deliver the business result they were supposed to.
Possible schema drift detected
customer_email → email01 / THE GAP
Green doesn't always
mean working.
Automation platforms know whether steps executed. That does not always reveal whether the intended result happened in the real world.
02 / PRODUCT DIRECTION
Verify the outcome,
not just the execution.
The first product direction is detection and verification. Diagnosis and repair become progressively more capable over time.
- 01FIRST DIRECTION
Observe
Understand expected cadence, workflow behavior and the data that matters.
- 02FIRST DIRECTION
Verify
Check whether expected real-world outcomes actually happened.
- 03PLANNED
Diagnose
Surface likely causes of silent failures, drift and unexpected behavior.
- 04LONG-TERM VISION
Repair
Safely propose and test fixes before a human applies them.
03 / THE DISTINCTION
Not another
uptime monitor.
EXECUTION MONITORING
Did it run?
- Trigger fired
- Nodes executed
- API returned 200
- Workflow completed
OUTCOME VERIFICATION
Did it work?
- Correct customer created
- Required data exists
- Proposal delivered
- Business rules passed
- Expected result happened
04 / ARCHITECTURE
Starting with n8n.
Designed beyond it.
The first integration is planned around n8n: a practical environment for building and testing the concept. Trustiform's direction is vendor-independent.
Integration names describe product direction, not partnerships or current support.
05 / EVOLUTION
From knowing to
recovering.
TODAY / FIRST DIRECTION
- Detect
- Verify
- Diagnose
- Human fixes
NEXT / PLANNED
- Detect
- Diagnose
- Generate fix
- Test safely
- Human approves
LONG-TERM VISION
- Detect
- Diagnose
- Repair
- Verify
Self-healing
automations.
Systems that can find, diagnose and safely recover from outcome failures — with appropriate human control.
06 / EARLY ACCESS
We're building
Trustiform.
If you run production automations or agents, we want to understand how they actually fail.
Validation and early development. No finished platform, no inflated promises — just a specific problem worth solving.