// CASE STUDIES

Outcomes, not adjectives.

A sample of the work — how fast we filled it, who we placed, and how quality held. Names are anonymized until clients approve disclosure; figures shown are illustrative placeholders for now.

FRONTIER LAB · RLHF

Stalled eval backlog → calibrated 40-person preference-data team in under three weeks.

Illustrative outcome — replace with a real client result and a one-line quote. [PLACEHOLDER]

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18d
Scope → full team
40
Specialists placed
96%
Rubric agreement
QUANT FUND · DATA

Built a niche financial-document annotation pod with domain-expert reviewers.

Illustrative outcome — replace with a real client result and a one-line quote. [PLACEHOLDER]

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9d
Open → first output
12
Annotators
3x
Throughput vs prior vendor
HEALTH MODEL CO · DOMAIN

Sourced licensed clinicians to evaluate medical model responses at the right bar.

Illustrative outcome — replace with a real client result and a one-line quote. [PLACEHOLDER]

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11d
To first review
8
Clinical evaluators
$310/hr
Blended expert rate
LEGAL-TECH AI · EVAL

Stood up a benchmark-construction team for contract-analysis evals.

Illustrative outcome — replace with a real client result and a one-line quote. [PLACEHOLDER]

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2wk
To kickoff
15
Contributors
100%
Retained at 60d
ROBOTICS STARTUP · MULTIMODAL

Multilingual image-and-text labeling across five languages, one managed pod.

Illustrative outcome — replace with a real client result and a one-line quote. [PLACEHOLDER]

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7d
To staffed
22
Annotators
5
Languages
AGENT PLATFORM · CODING

Working engineers authoring and grading agent tasks against a strict spec.

Illustrative outcome — replace with a real client result and a one-line quote. [PLACEHOLDER]

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10d
Shortlist
18
Engineers
94%
Spec pass rate

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