The human layer to enable high quality AI deployment

Get Started Join as a reviewer

Nothing is created until you choose to start.

Where do you need human help with your AI agent?

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What we put humans on

Transcription accuracy so a yes that was a no stops counting as a confirmation
Number capture so the discount that reaches your system is the one agreed on the call

How it works

Describe your use-case in plain English.
We setup the human pipeline to enable it in days.

Step 01

You describe it

Step 02

We break it into sub-tasks

Step 03

We build the workflow

Step 04

We publish the insights 

You describe it

Explain your use-case and what you need humans to solve as a simple English prompt 

Your words

Our voice agent calls users who abandoned carts in Hindi or English. We keep hearing that confirmations are wrong and discount amounts are wrongly captured.|

Hindi · English your production calls no commitment

We break it into sub-tasks

Judgement task is broken into objective sub-tasks an ordinary reviewer can execute accurately

Transcription accuracy

Transcript vs audio reviewer hears the call and marks every line the AI got wrong
Confirmation obtained agreement actually given, not assumed from a filler word

Number capture

Discount amount the figure logged matches the one agreed out loud
Quantity and total every amount and count on the call captured correctly

We build the workflow

Two things get built for every use case: a screen that narrows the marketplace down to reviewers who can do your exact sub-tasks, and the interface they log judgment in.

Tooling we generate

Screening

Built for relevant task screening for defined use-case and  capture speed. 

Logging

Built to cover all nuances needed to be captured relevant to task defined. 

Screening Logging
▶ 0:07

Did the customer agree?

Yes
No
One tap, next clip

We publish the insights

Findings on defined tasks along with reliability score of the human layer so that you can trust it

Findings · 400 calls

Confirmation wrongly logged 18%
Discount amount mismatch 11%
Transcript errors per call 1.4

Most common error

Heard "हां जी" · yes

Said "नहीं नहीं अभी तोह नहीं चाहिए" · no, I do not want it right now

Panel reliability · same batch

94%

reviewers agreeing with each other

91%

match with the hidden expert

Expert-rated calls seeded 1 in 20
Calls double-reviewed 1 in 5

For reviewers

Skilled judgment work. Paid. From your phone.

Step 01

Get in with a task

Step 02

Get trained

Step 03

Work and get paid

A task, not a CV

No resume, no interview. A short form, then a 2-minute assignment on real calls.

The reviewer application: full name, languages you speak, education, state, hours per week and phone, with an apply button that says your assignment is ready.

One decision at a time

One clip, one decision. Feedback after every answer tells you why you were right or wrong.

The 7-question assignment: two transcription checks and five listen-and-judge questions on real production calls, each openable.

Work from your phone, get paid

Work when you want, from a phone. Your agreement score sets your tier and your rate. Payouts weekly, by UPI.

The reviewer home screen: tier rates of 300 and 500 rupees an hour, top reviewers making 2,000+ a day paid weekly, and the work on offer with a rate against each role.
Start the screening task

Contact

Tell us where your AI needs a human.

A few sentences is enough. We read every one and reply ourselves.

Email us