Reporting Agents
COMPILE · SUMMARISE · PREPARE
Assemble recurring reports from systems of record and draft the narrative for a person to review and send.
Permitted work
Human action
OWNER APPROVES SEND
AI AGENTS
Focused AI for clearly defined operational responsibilities.
Stacx24 designs AI agents that research, monitor, analyse, prepare and coordinate within controlled operational systems.
Every agent is given a defined responsibility, clear permissions, accountable ownership and a measurable outcome.
ILLUSTRATIVE · PERMISSION BOUNDARY
Twenty-second silent sample with on-screen text: focused AI agents; connected applications and workflow automation; sensors, edge processing and telemetry; human approval and measurable outcomes.
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PRINCIPLE
An agent should know what it is responsible for.
Custom AI agents, developed as bounded components of an operational system rather than as standalone assistants.
We do not build agents with broad autonomy. We build bounded intelligence: a component with one job, the information that job needs, the tools it is permitted to use, and a person who answers for it. The agent proposes. Where the consequence matters, a person decides. That boundary is what makes an agent dependable inside a real operation.
| Topic | WE AVOID | WE ENGINEER |
|---|---|---|
| Responsibility | General-purpose assistants with open-ended scope | One written responsibility per agent |
| Permissions | Agents that act without an approval boundary | Explicit read, propose and act permissions |
| Ownership | Autonomy that no single person is accountable for | A named owner who can pause the agent |
| Measurement | Outcomes that are described but never measured | One operational number the agent exists to move |
AGENT TYPES
Six responsibilities we have engineered agents for.
Illustrative outputs
Research Agents
SEARCH · VERIFY · STRUCTURE
Research people, organisations, topics or markets against defined sources and return structured, cited findings.
Permitted work
Human action
ANALYST REVIEWS
Monitoring Agents
WATCH · DETECT · ALERT
Watch feeds, telemetry or records for defined conditions and raise a classified alert to the right person.
Permitted work
Human action
OPERATOR ACTS
Operations Agents
TRIAGE · ROUTE · COORDINATE
Triage incoming work, propose routing and coordinate handoffs between applications, vendors and people.
Permitted work
Human action
MANAGER APPROVES ACTIONS
Document Agents
EXTRACT · CLASSIFY · DRAFT
Extract and classify information from documents and prepare drafts, with every field traceable to its source.
Permitted work
Human action
REVIEWER CONFIRMS
Intelligence Agents
ANALYSE · COMPARE · EXPLAIN
Analyse patterns across coverage, portfolios or telemetry and explain what changed, for a person to decide on.
Permitted work
Human action
LEAD DECIDES
ARCHITECTURE
The agent is one component of a connected system.
An agent never runs on its own. It is triggered by an operational event, given business context, limited to specific tools and data, evaluated before its output is used, approved by a person where it matters, and monitored after it acts.
Reasons within its written responsibility.
Agent
The owner approves, edits or rejects.
Human approval
When confirmation is neededAn event, schedule or request starts the run.
Trigger
Records, policies and history the job needs.
Business context
Only the integrations it is permitted to call.
Tools / data
Output checked against rules and thresholds.
Evaluation
The approved change is made and logged.
Action
Accuracy, exceptions, cost and drift observed.
Monitoring
CONTINUOUS IMPROVEMENT
Five defined controls. One self-correcting loop.
Responsibility, permission, ownership, evaluation and outcomes — connected by a loop that finds and corrects gaps.
Responsibility
One sentence that says what the agent does and what it does not.
Example"CLASSIFY INBOUND COVERAGE FOR CLIENT X."
Permission
What it may read, what it may propose, what it may do, and with whose approval.
ExampleREAD: CRM, MEDIA DB · PROPOSE: TAGS · ACT: NONE
Owner
A named person who approves its output, reviews its record and can pause it.
ExampleOWNER: ACCOUNT LEAD · PAUSE: ONE CLICK
Evaluation
A test set, a threshold and a review cadence for accuracy, exceptions and drift.
ExampleTEST SET: 200 · REVIEW: WEEKLY
Outcome
The one operational number the agent exists to move, with its baseline.
ExampleMETRIC: HOURS TO CLIENT REPORT
Self Correcting
Finds and corrects gaps or errors, then returns to Responsibility.
ExampleFIND GAPS · CORRECT · REPEAT
Corrections stay within permissions. Human approval applies where required.
Where AI stops and a person takes responsibility.
The boundary is drawn before the agent is built. The AI lane covers reading, analysing, preparing and proposing. The human lane belongs to a named person: deciding, sending, changing and escalating.
AI prepares
READS · ANALYSES · PREPARES · PROPOSES
TRIGGER
New coverage detected
CONTEXT
Client brief, past tags
AGENT
Classifies, drafts summary
PROPOSED · CONFIDENCE 0.91
EVALUATION
Passed rules · flagged 1 exception
AWAITING APPROVAL
People decide
DECIDES · SENDS · CHANGES · ESCALATES
OWNER
Account lead reviews and approves
Example decisionEDITS 1 TAG · APPROVES
ACTION
Added to client report
EXCEPTION
Sensitive topic → escalated to director
MONITORING
Decision logged · feeds evaluation
THE AGENT NEVER SENDS, PUBLISHES OR CHANGES A RECORD ON ITS OWN
THE BOUNDARY IS A CONTRACT, NOT A SETTING
PRODUCTION CONTROLS
Built for operation, not demonstration.
Logs
Every run, input, proposal and decision is recorded and reviewable.
Permissions
Scoped credentials per agent. Nothing inherits broad access.
Evaluation
Test sets and thresholds run before release and on a schedule.
Fallbacks
Low confidence, timeouts and failures route to a person, never to silence.
Monitoring
Accuracy, exception rate and drift visible to the owner at all times.
Cost visibility
Model, tool and integration cost per run and per outcome, reported monthly.
CORE SYSTEM MODEL
The system is the product. Technology is a component.
- Not every step needs AI.
- Some need rules.
- Some need software.
- Some need edge processing.
- Some need people.
We engineer the right combination.
Research assistance
IN THE OPERATION
A document arrivesFrom the research team
01 / 08EVENT
A new document arrives
Field study notes
- Source document received
- Original retained
- Ready to review
Received
A research document starts the work. The original stays available throughout.
02 / 08CONTEXT
Bring the background together
Document + background
- Source details attached
- Related records found
- Approved labels loaded
Context attached
Existing records, source details and the approved label list give the document context.
03 / 08PROCESSING
Check the details first
Document checks
- Duplicate check complete
- Required details present
- Text ready for review
Checks complete
Software checks for duplicates and missing information before any AI suggestion.
04 / 08INTELLIGENCE
Suggest a label, within scope
Suggested label
- Field study
- Supporting passage highlighted
- Awaiting researcher review
Suggestion only
AI proposes a label from the approved list. It cannot publish the label itself.
05 / 08DECISION
A researcher makes the decision
Label review
- Source passage checked
- Suggested label reviewed
- Field study approved
Reviewed by researcher
The researcher reads the supporting passage and approves or corrects the suggestion.
06 / 08ACTION
Update the research record
Research record
- Label: Field study
- Source linked
- Review retained
Saved to record
Only the approved label enters the record, alongside its source.
07 / 08OBSERVATION
Record what actually happened
Activity record
- Suggestion recorded
- Reviewer decision recorded
- Save confirmed
Outcome recorded
The system records the suggestion, the review and the saved result so the team can inspect them.
08 / 08IMPROVEMENT
Review the labelling rules
Next-cycle guidance
- Review corrections
- Agree guidance changes
- Use approved guidance next time
Feedback to the next event
The team reviews corrections and agrees changes to the guidance before the next document.
Each outcome informs the next cycle.
- 01 · EVENTA new document arrives
A research document starts the work. The original stays available throughout.
- 02 · CONTEXTBring the background together
Existing records, source details and the approved label list give the document context.
- 03 · PROCESSINGCheck the details first
Software checks for duplicates and missing information before any AI suggestion.
- 04 · INTELLIGENCESuggest a label, within scope
AI proposes a label from the approved list. It cannot publish the label itself.
- 05 · DECISIONA researcher makes the decision
The researcher reads the supporting passage and approves or corrects the suggestion.
- 06 · ACTIONUpdate the research record
Only the approved label enters the record, alongside its source.
- 07 · OBSERVATIONRecord what actually happened
The system records the suggestion, the review and the saved result so the team can inspect them.
- 08 · IMPROVEMENTReview the labelling rules
The team reviews corrections and agrees changes to the guidance before the next document.
Everyday operations
IN THE OPERATION
A request arrivesFrom the operating team
01 / 08EVENT
A request starts the work
New work request
- Request received
- Source application linked
- Handoff opened
Received
An incoming request starts a handoff between the tools your team already uses.
02 / 08CONTEXT
Attach the details once
Request background
- Existing record attached
- Current state checked
- Owner identified
Context attached
The system brings together the request, existing records and its responsible owner.
03 / 08PROCESSING
Let the rules route the work
Connected applications
- Request inbox → work queue
- Required details checked
- Work queue → owner workspace
Handoff prepared
Defined rules check the request and pass its details between connected applications.
04 / 08INTELLIGENCE
Rules are enough here
Routing rule
- A required detail is missing
- Exception route selected
- Named owner notified
No AI needed
This example needs no AI decision. Defined rules identify an exception and send it to its owner.
05 / 08DECISION
The owner resolves the exception
Exception review
- Exception opened
- Missing detail supplied
- Owner confirms next step
Reviewed by owner
A named person supplies the missing detail and confirms that the work can continue.
06 / 08ACTION
Complete the handoff
Completed handoff
- Confirmed details transferred
- Next application updated
- Owner notified
Handoff complete
The confirmed information reaches the next application and the work continues.
07 / 08OBSERVATION
Keep the outcome visible
Activity record
- Exception recorded
- Resolution recorded
- Handoff confirmed
Outcome recorded
The system records completion and exceptions so the team can see what happened.
08 / 08IMPROVEMENT
Review the handoff rules
Next-cycle guidance
- Review recurring exceptions
- Agree routing changes
- Apply approved rules next time
Feedback to the next event
The team reviews repeated exceptions and approves rule changes for future requests.
Each outcome informs the next cycle.
- 01 · EVENTA request starts the work
An incoming request starts a handoff between the tools your team already uses.
- 02 · CONTEXTAttach the details once
The system brings together the request, existing records and its responsible owner.
- 03 · PROCESSINGLet the rules route the work
Defined rules check the request and pass its details between connected applications.
- 04 · INTELLIGENCERules are enough here
This example needs no AI decision. Defined rules identify an exception and send it to its owner.
- 05 · DECISIONThe owner resolves the exception
A named person supplies the missing detail and confirms that the work can continue.
- 06 · ACTIONComplete the handoff
The confirmed information reaches the next application and the work continues.
- 07 · OBSERVATIONKeep the outcome visible
The system records completion and exceptions so the team can see what happened.
- 08 · IMPROVEMENTReview the handoff rules
The team reviews repeated exceptions and approves rule changes for future requests.
Connected fields
IN THE OPERATION
A field reading arrivesFrom a connected sensor
01 / 08EVENT
A sensor reads the field
Incoming field reading
- Sensor reading received
- Field identified
- Reading time attached
Received
A new field reading starts the cycle, connecting conditions on the ground to the system.
02 / 08CONTEXT
Put the reading in context
Field background
- Field history attached
- Recent readings loaded
- Current conditions attached
Context attached
Field history and recent conditions help the team interpret the new reading.
03 / 08PROCESSING
Check the signal near the field
Edge processing
- Local checks run
- Incomplete readings flagged
- Relevant readings forwarded
Local checks complete
Local edge checks validate readings before relevant information reaches the monitoring application.
04 / 08INTELLIGENCE
Prepare a suggested response
Response proposal
- Field context considered
- Suggested response prepared
- Sent for agronomist review
Suggestion only
The system uses the checked information to propose a response within its defined scope.
05 / 08DECISION
The agronomist reviews
Agronomist review
- Conditions reviewed
- Proposal checked
- Response approved
Reviewed by agronomist
The agronomist checks the proposal and approves or adjusts it before it reaches the operator.
06 / 08ACTION
Send the approved proposal
Operator work item
- Approved proposal attached
- Instructions available
- Delivered to operator
Ready for the operator
The approved proposal reaches the operator with the instructions they need.
07 / 08OBSERVATION
Keep watching the conditions
Field activity record
- New readings recorded
- Operator reports attached
- Outcome ready for review
Observation continues
New readings and operator reports help the team understand what happened next.
08 / 08IMPROVEMENT
Review the next field cycle
Next-cycle guidance
- Review field observations
- Agree guidance changes
- Use approved guidance next time
Feedback to the next event
The agronomist reviews the observations and agrees guidance for the next cycle.
Each outcome informs the next cycle.
- 01 · EVENTA sensor reads the field
A new field reading starts the cycle, connecting conditions on the ground to the system.
- 02 · CONTEXTPut the reading in context
Field history and recent conditions help the team interpret the new reading.
- 03 · PROCESSINGCheck the signal near the field
Local edge checks validate readings before relevant information reaches the monitoring application.
- 04 · INTELLIGENCEPrepare a suggested response
The system uses the checked information to propose a response within its defined scope.
- 05 · DECISIONThe agronomist reviews
The agronomist checks the proposal and approves or adjusts it before it reaches the operator.
- 06 · ACTIONSend the approved proposal
The approved proposal reaches the operator with the instructions they need.
- 07 · OBSERVATIONKeep watching the conditions
New readings and operator reports help the team understand what happened next.
- 08 · IMPROVEMENTReview the next field cycle
The agronomist reviews the observations and agrees guidance for the next cycle.
Read the complete system model
- EVENT
Something happens in the operation.
- CONTEXT
Records, history and state are attached.
- PROCESSING
Rules, software and integrations do the deterministic work.
- INTELLIGENCE
One bounded AI component, where judgement can be modelled.
- DECISION
A named person decides where it matters.
- ACTION
Something changes in the world.
- OBSERVATION
Telemetry and monitoring record what happened.
- IMPROVEMENT
The loop feeds back into the next event.
Related work
photo: research team reviewing classified records
AI Research & Data Systems
Research data pipelines with an AI classification agent proposing labels inside a defined scope, and structured review by the research team before anything enters the record.
DATA · API · AI AGENT · CLASSIFY · HUMAN REVIEW
NEXT STEP
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