ADCOCognitive Outsourcing
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ADCO AI · COGNITIVE OUTSOURCING

Human intelligence infrastructure.
Built for AI systems.

ADCO AI provides managed teams that prepare data, evaluate model outputs, verify quality, and keep human attention on the decisions automation cannot own alone.

Start a pilot Explore capabilities
Defined standardsManaged reviewersVisible quality control
A managed team actively reviewing AI data and model outputs
Human attention, deliberately placed.Prepare · Evaluate · Verify · Monitor

The missing layer

AI scales computation.
We scale the judgment around it.

ADCO turns client criteria into trained, supervised, and reviewable human workflows across the AI lifecycle.

See the operating model
LIVE WORKFLOWADCO / JUDGMENT LAYER
Incoming
Model output
Raw data
Edge case
User signal
Human judgmentManaged by ADCO
Controlled
Verified
Structured
Escalated
Ready
Calibrated reviewersDefined criteriaVisible review

Core capabilities

Human work,
applied with purpose.

Four ways ADCO supports the data and model lifecycle. Explore the full capability set on the dedicated page.

An analyst comparing AI responses against evaluation criteria
Criteria become decisions.Comparison · Scoring · Evidence · Escalation
01

Data preparation

Structure raw information for reliable downstream use.

03

Model evaluation

Measure what a model produces against a defined standard.

04

Human verification

Add accountable review where automated confidence ends.

05

AI monitoring

Keep human attention on recurring failure patterns.

View all capabilities
A professional reviewer examining model evaluation outputs
Human attention, deliberately placedEvaluation · Verification · Escalation

Operating model

Managed from standard
to final review.

ADCO converts client criteria into a supervised operating system. Work begins with scope and calibration, then expands only after the review path is clear.

Project-specific training Documented quality review Exception handling Visible reporting
See how delivery works

Latest insights

A closer look at
human judgment in AI.

Field notes on evaluation, control, and managed human workflows.

Field note · July 2026 · 6 min

Where human judgment belongs in the AI lifecycle

A practical map of the decision points where people add context, accountability, and control.

Operations · July 2026 · 7 min

Model evaluation: from rubric to exception log

Why reliable evaluation is an operating system, not a spreadsheet of scores.

Start with one workflow

Bring us the work
AI cannot own alone.

We will define the standard, calibrate the review process, and prove the workflow through a controlled pilot.

Discuss your workflow