HUMAN-IN-THE-LOOP OUTSOURCING
Human-in-the-Loop
Trained reviewers check, correct and escalate AI outputs and label your data inside your tools – free sample first.Human-in-the-Loop Outsourcing: Trained Reviewers for AI Review, Correction and Data Labeling
Outsourced human-in-the-loop services pair your AI with trained reviewers who check, correct or escalate its outputs before high-stakes actions, and who label the data it learns from. Our Dhaka team does this for US, UK and Singapore companies with written guidelines, measured accuracy and a full audit trail. This is a managed review service, not a job board.
Delivered from Dhaka (UTC+6): full-day overlap with Singapore, morning overlap with the UK, night shift available for US queues.
Free calibration sample · Pilot $1,500 · Production from $10/hour · See pricing →
5 working days 01 Calibration sample
2 weeks 02 Pilot review batch
Daily 03 Production review
3-month minimum 04 Dedicated reviewer pod
Results and proof
We are launching this service line, so we publish evidence instead of promises: market data with sources, our own benchmark results, and a free calibration sample on your real AI outputs before you pay anything. Case studies with client numbers will be added here as pilots complete, with client permission.
Demand154% Upwork’s In-Demand Skills report found US client demand for AI data annotation and labeling grew 154% year over year, measured on completed jobs only.
Why projects fail40%+ Gartner predicts more than 40% of agentic AI projects will be cancelled, citing unclear business value and inadequate risk controls. Human review is the risk control most of them lack.
RegulationArticle 14 The EU AI Act’s Article 14 requires high-risk AI systems to be designed for effective human oversight.
What human-in-the-loop outsourcing does
You receive people and process, not a tool: a trained reviewer team, written guidelines, measured accuracy and the records your auditors will ask for. Each engagement delivers the six items below, and every production engagement includes double-checking, gold-set audits, an escalation path and a monthly report.
AI output review and correction
Reviewers check AI-generated answers, classifications, summaries and extracted fields, correct what is wrong and record why.
Exception and edge-case handling
Items the AI flags as low-confidence, or that fall outside its rules, go to a person with a written decision path instead of being lost or guessed.
Human approval before high-stakes actions
A reviewer approves any AI action that changes money, records or customer communication, with a log of every decision.
Data annotation and labeling
Text, document and form labeling for training and evaluation sets, to your guidelines, with agreement measured between reviewers.
Evaluation and QA sampling
A share of AI outputs is re-checked against a hidden gold set every week, so you see accuracy per category as a number.
Escalation, dashboard and audit trail
Turnaround and accuracy dashboard, an escalation log, and an export of every decision with reviewer ID, timestamp and guideline version.
Not included: model training compute or tooling licences; graphic or harmful content moderation; legal sign-off on your AI’s compliance.
How human-in-the-loop outsourcing works with your team
Human-in-the-loop outsourcing works in four steps: a free calibration sample on your real outputs, a two-week fixed-price pilot that produces guidelines and an accuracy report, production review billed by the hour or item, and an optional dedicated reviewer pod. Your team joins one call per week; reviews run daily from Dhaka.
Typical cost and timeline
A pilot review batch takes two weeks and costs $1,500 fixed, after a free calibration sample. Production review is $10 per reviewer hour, $9 at 1,000 hours a month, or a dedicated reviewer at $1,500 a month. Domain-expert review for payroll, HR and finance work is $20 an hour.
Team In Dhaka, Bangladesh.
Tools Your review tool or queue.
Quality targets Agreed per task in the pilot.
Communication One weekly call in your time zone, a shared channel, a written change log for every guideline version.
Security, compliance and contract
Every engagement starts with a mutual NDA and, for personal data, a data processing agreement with the transfer terms your country requires. Reviewers work on a no-phone floor in your tools or a locked-down desktop, see data only while reviewing it, and every decision is logged. Certifications are listed only when actually held.
NDA signed before any data access; reviewers sign individual confidentiality agreements.
Data processing agreement (Article 28(3) terms) for personal data; no sub-processor without your written approval.
Review floor: phones locked away, USB and printing disabled, access removed when a reviewer leaves the queue.
Data handling: work inside your tool or a locked-down desktop, no local copies, data deleted or returned at the end under the contract.
Background checks: identity, education and reference checks on every reviewer.
UK clients: ICO International Data Transfer Agreement (IDTA) or the UK Addendum.
Singapore clients: PDPA Section 26 transfer clause or ASEAN Model Contractual Clauses.
Contract: accuracy targets and turnaround written into the SLA; rework at no cost when a batch misses the agreed target; changes priced first as a change request.
How much does this cost? See pricing →
Frequently asked questions
How much do outsourced human-in-the-loop services cost?
A free calibration sample first, then a two-week pilot review batch at $1,500 fixed. Production review is $10 per reviewer hour, $9 per hour at 1,000 or more hours a month, or a dedicated reviewer at $1,500 per month. Domain-expert review for payroll, HR and finance work is $20 per hour. Prices are in US dollars.
What turnaround can you offer?
Turnaround is agreed per queue in the pilot. Dhaka runs a full working day ahead of Singapore’s morning and overlaps the UK morning, and a night shift covers US business hours where volume justifies it. Typical targets are same-day for production queues and 24 hours for batch work; urgent queues carry a $12 hourly rate.
How do you measure reviewer accuracy?
Every reviewer is scored against a hidden gold set of known-correct items, a share of items is double-reviewed, and disagreements go to a QA lead. You receive weekly accuracy and inter-annotator agreement figures per category, so quality is a measured number in your report, not a claim on our website.
How is our data kept secure?
Reviewers see only the items in their queue, only while reviewing, on a floor where phones are locked away and USB and printing are disabled. We work inside your tool or a locked-down desktop, keep no copies, and delete or return data at the end under the contract. Sub-processors need your written approval.
Can we start with a pilot?
Send 200 items or two hours of work from your real AI outputs. Within five working days you get a short accuracy snapshot: where the AI is right, where it fails, and what a guideline would need to cover. It costs nothing and does not commit you to the pilot.
Are you hiring human-in-the-loop workers?
No. This page is for companies that need reviewers; we do not list jobs here. We recruit through our own careers page in Dhaka, train reviewers on written guidelines and keep them on our payroll, so you get a managed team with one contract, not individual freelancers.
How is this different from a data annotation vendor?
Annotation vendors label training data before a model ships. We do that too, but most of our work is after launch: reviewing live AI outputs, handling exceptions and approving high-stakes actions, with an audit trail. If you only need bulk image labeling at the lowest price, we are not the cheapest option.
What is the difference between this and AI Oversight for Payroll, AP and EOR?
Human-in-the-Loop covers any AI system and any workflow. AI Oversight for Payroll, AP and EOR is the same idea applied to named payroll, accounts-payable and employer-of-record queues, staffed by reviewers with that domain background and priced at the expert rate. Start here if your use case is not in those three areas.