DATA OPERATIONS PARTNER

Reliable Data Operations for AI and Business

We help AI companies and global businesses prepare, evaluate and improve high-quality datasets through structured annotation, human evaluation and data quality assurance.

01 · INTAKE
Scoping & setup
02 · ANNOTATE
Structured labeling
03 · EVALUATE
Human review
04 · QA
Consistency checks
05 · DELIVER
Reporting & handoff
STRUCTURED ANNOTATION — HUMAN EVALUATION — QUALITY ASSURANCE — MULTIMODAL DATA — BENCHMARK DESIGN — DATA ANALYTICS — STRUCTURED ANNOTATION — HUMAN EVALUATION — QUALITY ASSURANCE — MULTIMODAL DATA — BENCHMARK DESIGN — DATA ANALYTICS —
CORE SERVICES

What we operate

Four working modules, run together or independently depending on where your pipeline needs support.

MODULE — TRAINING

AI Training Data

Structured annotation and dataset preparation for text, image, audio, video and multimodal AI projects.

MODULE — EVALUATION

AI Evaluation

Human evaluation, benchmark task design and rubric-based assessment for AI models and agents.

MODULE — QA

Data Quality Assurance

Dataset review, error detection, consistency checks and measurable quality control.

MODULE — ANALYTICS

Data Analytics

Data processing, classification and business insights tailored to client requirements.

HOW WE OPERATE

A pipeline you can audit at every step

Each engagement moves through the same five stages, with sign-off and reporting between steps.

01
Intake & scoping
We define task rubrics, data formats, edge cases and volume with your team before work begins.
02
Structured annotation
Trained annotators and domain specialists label data against agreed guidelines and schemas.
03
Human evaluation
Independent reviewers assess model outputs or annotation quality against defined rubrics.
04
Quality assurance
Sampling, consistency checks and error analysis run before any dataset is marked as complete.
05
Delivery & reporting
You receive the dataset alongside a quality report covering coverage, accuracy and known limitations.
HOW WE HANDLE DATA

Built for engagements that require care

Every project runs under a signed NDA and a defined data handling protocol. Access to client data is scoped to the annotators and reviewers assigned to that project, and each dataset passes through a documented QA step before delivery. We work within the data boundaries our clients set, and do not use client data beyond the agreed scope of an engagement.

NDA-GOVERNED

Standard confidentiality terms on every engagement, before any data changes hands.

ACCESS-CONTROLLED

Project-scoped access for annotators and reviewers, revoked at project close.

QA-DOCUMENTED

Sampling and error checks recorded and shared alongside each delivery.

SCOPE-LIMITED

Data used only for the purpose defined in the engagement agreement.

START A CONVERSATION

Tell us what your dataset needs to do, and we'll scope the pipeline around it.