Human-in-the-Loop
A checkpoint where a person reviews, approves, or corrects an automated decision before it moves forward.
Human-in-the-loop (HITL) adds a human review step to automated workflows. Humans approve, correct, or reject machine outputs before actions execute.
It is used in fraud checks, content moderation, invoice approvals, and support triage. Humans handle ambiguous or high-risk cases while automation covers routine ones.
HITL fits as a controlled gate with queues, SLAs, and context-rich tasks. It balances speed with safety, ensuring quality when full automation is too risky.
Frequently Asked Questions
When should I add human review?
For high-risk actions, low-confidence outputs, or policy-sensitive decisions. Define clear thresholds that trigger review.
How do I keep HITL efficient?
Provide concise context, highlight confidence, and pre-suggest actions. Track reviewer SLAs and reduce noise with good guardrails.
What tools help HITL?
Task queues, approval UIs, audit logging, and feedback capture. Integrate with ticketing/CRM so decisions sync back to systems.
How do I use reviewer feedback?
Feed corrections back into prompts, rules, or training data. Prioritize common errors for quick iteration.
How many cases should be auto-approved?
Start with a conservative threshold. Expand auto-approvals as accuracy improves and guardrails prove reliable.
How do I ensure consistency across reviewers?
Provide playbooks, examples, and calibration sessions. Measure agreement and audit decisions periodically.
What metrics matter for HITL?
Review time, decision agreement, escalation rates, and downstream error reductions. Track reviewer fatigue indicators.
Can HITL be temporary?
Yes—use it during rollout or high-risk periods, then taper as confidence grows. Keep the capability for incident response.
How do I handle sensitive data in HITL?
Limit visibility, mask PII, and restrict access. Use role-based permissions and audit logs.
Agentic AI
An AI approach where models autonomously plan next steps, choose tools, and iterate toward an objective within guardrails.
Agentic Workflow
A sequence where an AI agent plans, executes tool calls, evaluates results, and loops until success criteria are met.
Agent Handoff
A pattern where one AI agent passes context and state to another specialized agent to keep multi-step automation modular.
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