DATA
Model inference stays inside the agency's approved local system.
Models perform inference locally. The implementation documents which sources the system can read, what it can retain, and where outputs are written.
Technical overview
A clear boundary around your agency’s AI.
This page outlines how the local system is intended to handle data, connect to existing software, control employee access, increase agent independence, and stay maintainable over time.
Architecture first. Final hardware, models, integrations, and capacity are selected after the agency workflow and environment are assessed.
AGENCY NETWORK BOUNDARY
EmailDocumentsAgency software
LOCAL
AI system
Models + agents
AnswersDraftsApproved tasks
01Local inference
02Approved integrations
03Role-based access
04Reviewed autonomy
05Managed operations
System boundary
Keep AI processing close to the systems and people it serves.
The system runs on equipment at the agency. Connections, update paths, remote support, and permitted actions are documented before live use.
INTEGRATIONS
Existing software remains the system of record.
Agents connect to the approved inboxes, files, agency software, CRM, and procedures required for a specific workflow rather than replacing the entire stack.
IDENTITY
Employee access follows role and responsibility.
As the rollout expands, individual profiles can limit which information an employee sees and which actions the employee or agent may perform.
Controls
Independence is granted workflow by workflow.
Agent autonomy is not a single switch. Each process advances only after testing, human review, and agency approval.
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01
OBSERVEMap the real process
Understand instructions, exceptions, sources, handoffs, and decisions before building.
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02
ASSISTDraft under review
The agent prepares work while a person checks every output and correction is captured.
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03
ACTRun approved steps
The agent completes only the actions and handoffs explicitly permitted for that workflow.
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04
OPERATEEarn more independence
Review can be reduced only after results meet the agreed standard and the agency approves the change.
Operations
Monitor the system, evaluate updates, and preserve a known working standard.
Local does not mean unmanaged. The operating layer should make health, versions, permissions, workflow changes, and support activity visible.
MONITORING
Know whether the system and workflows are healthy.
Track service availability, resource use, failures, and the operational signals chosen for each approved workflow.
MODEL UPDATES
Test the replacement before changing the standard.
New local models are evaluated against the agency’s real tasks before they replace a known configuration.
CHANGE CONTROL
Document what changed and why.
Integrations, permissions, instructions, and autonomy levels should change deliberately rather than drift silently.
REMOTE SUPPORT
Agency-approved access only.
Support access and update paths are selected with the agency and documented as part of the deployment boundary.
LOWER-LEVEL COMPONENTS
Plain architecture first. Product names second.
The management and monitoring layer is being developed as sparkDash. The local agent runtime is Hermes Agent. The agency-facing design remains based on functions, permissions, and verified behavior rather than requiring buyers to learn product names.
Decided during assessment
The detailed design follows the agency’s actual environment.
- 01
First administrative workflow and success standard
- 02
Required integrations, permissions, and human checkpoints
- 03
Hardware capacity, resilience, network, power, and physical location
- 04
Local model baseline and evaluation set
- 05
Employee access plan and staged rollout
- 06
Monitoring, update, recovery, and support procedures
Technical fit starts with the workflow
Bring one process and the systems it touches.
We will identify the data boundary, integration points, controls, and open questions before discussing a final configuration.