Skip to main content
Apragya AIFree quotation builderQuotation builderQuote builderno signup
Sign inRegister
Human review

Human in the Loop Approvals for AI: Agents Do the Work, People Make the Call

For managers and compliance teams who want AI to prepare decisions, and people to make the ones that matter.

Start freeTalk to sales
An operations head taking a folder from a small robot for review

Human in the loop approvals for AI mean an agent stops at a defined point and waits for a person. The agent has done the reading, matching and drafting. The person decides whether the result goes ahead.

Without that pause, teams choose between two bad options: trust the agent blindly, or recheck everything it does and lose the time it saved.

This page covers where review pays off, an illustrative example, and how review works on Apragya's agents and workflows.

Where AI without review goes wrong

Wrong payments

A misread bill is paid in full.

Wrong messages

A draft with an error reaches a customer.

Wrong people

A candidate is rejected on a bad score.

No accountability

Nobody can say who allowed the decision.

Human review of AI output, compared

Checking AI output by hand in another window works for a few cases a day. At volume, review must arrive with the agent's work attached, record the decision, and let the process continue without someone restarting it.

Manual rechecking against Apragya review

FeatureManual recheckingApragya human review
Where review happensAnother windowA review item with the agent's output
ChoicesAccept or redoApprove, reject, modify or escalate
After approvalWork restarted by handThe run resumes from its checkpoint
Waiting itemsForgottenExpire after a set time
RecordNoneDecision kept with the run

Checked against public information on 16 September 2026.

An example: a Mumbai insurance broker

Take an illustrative broker whose agent reads claim documents, checks them against the policy and drafts a note for the insurer. The operations head wanted every note reviewed before it went out.

What the reviewer saw on one claim

  • Documents readClaim form, bills and discharge summary.Done
  • Policy datesTreatment within the cover period.Matched
  • Bill totalOne bill counted twice in the claim form.Mismatch
  • Draft notePrepared for the insurer.Ready
  • Reviewer decisionModify the amount, then approve.Pending
  • SentOnly after approval.Pending
The mismatch was flagged, and the reviewer corrected it before approving.

The reviewer changed the amount in the draft and approved it. The run carried on with the corrected value, the note went to the insurer, and the claim file shows who changed what and when.

A claim folder with a corrected sheet and a green stamp
Corrected, then approved: the run continued with the right amount.

How the AI approval workflow works

Step 1 of 5

Agent works

The agent reads, checks and drafts up to the review point.

  1. Agent works: The agent reads, checks and drafts up to the review point.
  2. Review item: A person receives the item with the agent's output.
  3. Decide: Approve, reject, modify values, or escalate.
  4. Resume: Approved or modified work continues from its checkpoint; rejected runs stop.
  5. Expire: Items left too long expire, so nothing waits forever.

What sets HITL AI in India apart on Apragya

On the record

Review sits beside the claim, bill or candidate.

Approvals inbox

Reviewers see pending items in one place.

Guardrails too

Policies catch known risks before review.

Role-based access

Only the right roles can review.

Run history

Each run shows the review and its outcome.

In workflows

Review steps can sit anywhere in a workflow.

Human review appears in agents such as resume screening and duplicate invoice detection. See also AI guardrails.

Getting started

  1. List the agent decisions that affect money, people or customers.
  2. Put a review point before each of them.
  3. Choose who reviews, by role.
  4. Set an expiry that fits the process.
  5. After a month, drop review where the agent is always right.

Review is a dial, not a switch: start with more of it and reduce it with evidence.

What it costs to start

Free
Up to 3 users
CRM, HR and Vendor Onboarding
INR 3,999
Starter, a month
Up to 10 users, CRM and HR plus a choice of apps
INR 7,999
Pro, a month
Up to 25 users and every enterprise app

Human review questions

What does modify do?
The reviewer changes values in the agent's output, and the run continues with the corrected values.
How do we decide where review is needed?
Start with decisions that move money, affect a person or reach a customer. Keep review on those for a month, then look at how often reviewers changed anything. Where they almost never did, review can be relaxed.
Who should review agent work?
The person who would have made the decision without the agent, usually the team lead for that process.
What happens on reject?
The run stops and is marked as failed, so nothing goes ahead.
Can a reviewer pass it up?
Yes. Escalate sends the item on for a more senior decision.
Do ready-made agents support review?
Yes. Agents can pause for review, and review steps can be added to workflows.
What does it cost to start?
The free plan covers up to 3 users with CRM, HR and Vendor Onboarding and 1,000 AI Credits a month. Starter is INR 3,999 a month for up to 10 users, with CRM and HR plus a choice of apps such as Sales and POS, Inventory, Payroll, Purchase and Payables, Support and Manufacturing. Pro is INR 7,999 a month for up to 25 users with every enterprise app, including Finance and Accounting, plus 5,000 AI Credits, single sign-on and audit logs.

Put a person where it matters

Add review before every agent decision that touches money or people.

Start freeTalk to sales