AI Data Services Better data, better AI
AI is only as good as the data behind it. We collect, label, clean and engineer the data your models need, from annotated images and transcripts to LLM training and evaluation sets, with quality checks at every step and privacy built in.
Who our AI data services are for
- AI and ML teams that need labeled training data at scale
- Companies fine-tuning or evaluating large language models
- Product teams building computer vision, speech or NLP features
- Organizations that must prepare sensitive data for AI while protecting privacy
Problems AI data services solve
Data annotation and AI data services we deliver
Data Collection & Generation
- Dataset sourcing, collection and curation
- web data extraction
- synthetic data generation and augmentation
- speech and multilingual datasets
Data Labeling & Annotation
- Image, video, text and audio annotation
- bounding boxes, segmentation, entity tagging and transcription
- human-in-the-loop review and validation
LLM Training & Evaluation Data
- Instruction-tuning datasets (prompt/response pairs)
- preference and ranking data for RLHF and DPO
- evaluation and red-team datasets
Data Preparation & Quality
- Data cleaning, deduplication and normalization
- data validation and quality audits
- PII and PHI redaction and de-identification to support HIPAA, CCPA/CPRA, PIPEDA and UK GDPR compliance
Data Engineering for AI
- Data pipelines and ETL/ELT
- embeddings and vector database setup
- data warehouse and lakehouse setup
How our data annotation process works
Define the data.
We agree the data types, volumes, label schema, quality targets and privacy rules.
Write the guidelines.
We create clear annotation guidelines with examples and edge cases, and test them on a sample.
Pilot batch.
We deliver a first batch for your review and adjust guidelines on your feedback.
Scale with quality control.
We scale up with consensus checks, expert review and regular quality reports.
Deliver and integrate.
Data is delivered in your format, or loaded straight into your pipelines and storage.
AI data services use cases
Example scenarios, not client projects.
AI product company: LLM evaluation set.
Domain experts write and rate hundreds of realistic prompts and ideal answers, giving the team a reliable benchmark to compare model versions before release.
Retail tech startup: product image annotation.
Product photos are labeled with bounding boxes and attributes to train a visual search and catalog tagging model.
Healthcare analytics firm: de-identified records.
Clinical notes are de-identified with PHI removed in line with HIPAA requirements before they are used to train a summarization model.
Data annotation tech stack
- Annotation
- leading labeling platforms, or your own tools if preferred
- Data processing
- Python, SQL, Spark and dbt
- Storage and retrieval
- cloud data warehouses, lakehouses and vector databases
- Privacy
- automated PII/PHI detection with human verification
- Delivery formats
- JSON, JSONL, CSV, COCO, YOLO, Parquet or direct pipeline integration
AI data services engagement models
Build
We run the full data project, from guidelines and labeling to quality control and delivery.
Consult
We design your data strategy, label schemas, QA process and pipeline architecture.
Staff
Data engineers and annotation leads join your team to manage data work with you.
Data annotation and AI data FAQs
How do you ensure label quality?
Through clear guidelines, annotator training, consensus labeling, expert review and regular quality audits with agreed accuracy targets.
Can you handle sensitive or regulated data?
Yes. We use secure environments, access controls and NDAs, and we redact or de-identify PII and PHI. For healthcare data we follow HIPAA-aligned handling practices.
Do you work with specialized domains?
Yes. For areas such as healthcare, finance, legal and technical content, we use annotators with relevant domain knowledge.
Can you scale up quickly?
Yes. We start with a pilot batch to lock in quality, then scale the team to your volume and deadlines.
What formats do you deliver in?
Any standard format your tools use, or we load the data straight into your storage and pipelines.
Ready to train or fine-tune?
LLM fine-tuning and ML development →Need data pulled from business documents?
Intelligent document processing →
What happens next
Book a call.
A free 30-minute consult about your data needs.
Free assessment.
We review a sample of your data and recommend an approach.
Proposal.
A clear scope, quality targets, timeline and price, starting with a pilot batch.
Get the data your AI needs
Tell us what you're training, fine-tuning or evaluating. We'll propose a data plan with clear quality targets.