ViriSIM
Continuous Improvement

:: IMPROVEMENT LOOP ::

Your models get safer
with every audit.

Every violation becomes a policy. Every audit generates training data. Every guardrail prevents recurrence. ViriSIM's improvement loop makes your AI safer automatically.

Audit
Detect Violations
Generate
Policies & Guardrails
Fine-Tune
Auto Training Data
Inject
Pre-Gen Guardrails

Audit. Report. Improve.

Every API call feeds into a continuous improvement cycle that makes your AI safer over time.

1

Audit I/O at Decision Time

Every AI input and output is audited for PII, regulatory violations, bias, and safety risks.

2

Detect & Aggregate Violations

Select up to 20 audit logs. Violations, safety issues, and recommended actions are extracted and aggregated.

3

Generate Policies & Guardrails

Generated policy sets from real violations. Reactive when violations exist. Preventive when patterns are clean.

4

Fine-Tune Models

Auto-generated JSONL training data from audit logs. Pull by date range. Manual or scheduled fine-tuning.

5

Inject Guardrails & Repeat

Pre-generation guardrails injected into future prompts. Models improve automatically. The cycle continues.

Turn violations into enforceable policies

Select up to 20 audit logs. ViriSIM aggregates violations and generates policy sets automatically.

Violation Aggregation

Extracts violations, safety issues, recommended actions, verdicts, and regulatory details from selected logs.

Up to 20 logs per run

Reactive Policies

When violations exist, generates targeted policies to prevent recurrence. Each policy includes conditions, severity, and remediation steps.

Violation-driven

Preventive Policies

When no violations are found, generates proactive guardrails to maintain compliance and prevent future issues.

Pattern-driven
View Sample Policy Set

Every audit becomes a training example

Pull non-compliant logs by date range or upload custom data. Export as JSONL. Feed directly into OpenAI or custom endpoints.

1

Select Data Source

Pull non-compliant audit logs by date range or upload custom JSONL/JSON/TXT files.

2

Preview & Export

Review structured training examples. Download as JSONL for direct model consumption.

3

Fine-Tune Model

Connect to OpenAI or any OpenAI-compatible endpoint. Track job progress with ETA.

4

Download Report

Export fine-tuning reports with performance metrics, lineage, and compliance documentation.

Training Example (JSONL)

{"messages": [{"role": "system", "content": "Comply with: HIPAA"}, {"role": "user", "content": "Patient: Maria Hoffmann, DOB: 14/03/1961..."}, {"role": "assistant", "content": "Patient: [REDACTED], DOB: [REDACTED]..."}]}

Provider

OpenAI OpenAI
Custom Endpoint

Training Data Source

From Audit Logs
Upload Custom File

Parameters

3
Epochs
0.1x
Learning Rate
8
Batch Size

Job History

View all fine-tuning jobs with status, progress, ETA, and performance metrics.

Download Report

Export fine-tuning reports with full lineage, compliance mapping, and training provenance.

Training lineage: Every example traces back to the source audit log. Full provenance from violation to fine-tune.

Set it. Forget it. Models improve automatically.

Schedule recurring fine-tuning jobs. ViriSIM pulls recent violations, generates training data, and runs the job — completely hands-free.

Automation Active
Interval
Every 7 days
Last Run
Jul 5, 2026
Data Source
Latest 50 violations
Extraction Mode
Auto-pull from logs

Recurring Scheduling

Set intervals in days. Auto-trigger on schedule. Toggle active/inactive anytime.

Status Monitoring

Track automation status, start dates, frequency, and last run from a single dashboard.

Training Lineage

Every example traceable to source audit. Full provenance for compliance and auditability.

Hands-Off Improvement

Models get safer between releases. No manual intervention needed. Just set and let it run.

Stay informed. Receive push and in-app notifications when auto-fine-tuning is triggered, completes, or needs attention. Never miss a training cycle.

How ViriSIM's improvement loop compares

Manual retraining is slow and reactive. ViriSIM automates the entire cycle.

CapabilityManual RetrainingOther ToolsViriSIM
Training Data Source Manual curation Basic logging Auto from audit logs
Policy Generation Manual writing None Auto from violations
Guardrail Injection None None Pre-generation auto-inject
Scheduled Fine-Tuning None None Recurring automation
Training Lineage None None Full traceability
Cycle Automation None None Full loop automated

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