Our Services

A comprehensive suite of data services designed to take you from raw, unstructured data to production-ready datasets.

Data Acquisition

Sourcing the right data is the foundation of every successful AI project. HarvestHive operates a global network of data contributors, enabling us to collect diverse, representative datasets across any language, geography, or demographic profile.

We design custom data collection protocols tailored to your model's specific requirements — from simple text samples to complex multimodal recordings with controlled environmental conditions.

  • Speech & audio recordings
  • Image and video datasets with defined capture parameters
  • Text and document collection at scale
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Data collection specialist gathering field data

Data Annotation & Labeling

Annotation quality determines model quality. Our annotation teams are carefully trained and tested before working on client projects, and every batch is reviewed by QA leads who enforce strict inter-annotator agreement standards.

We support all major annotation paradigms for image, text, audio, and video data, and deliver output in formats compatible with all leading ML frameworks and platforms.

  • Image annotation: bounding boxes, segmentation, keypoints, classification
  • Text annotation: NER, sentiment, intent, POS tagging
  • Audio annotation: transcription, sound classification
  • Video annotation: object tracking, action recognition, scene classification
  • RLHF and preference ranking for LLM fine-tuning
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Data annotation specialist labeling images for machine learning

Data Cleaning & Processing

Dirty data is one of the leading causes of underperforming AI models. HarvestHive's data cleaning service combines automated detection algorithms with human expert review to identify and resolve data quality issues before they reach your training pipeline.

Whether you're working with legacy datasets, scraped content, or field-collected data, our cleaning workflows deliver structured, validated outputs ready for immediate use.

  • Duplicate detection and deduplication
  • Noise removal and outlier filtering
  • Data normalization and standardization
  • Format conversion and schema alignment
  • Missing value imputation and validation
  • PII detection and redaction
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Data quality specialist reviewing and cleaning datasets

Data Enrichment

Transform your existing datasets from adequate to exceptional. HarvestHive's enrichment service adds contextual depth, additional attributes, and structured metadata that make your data more valuable, more searchable, and more effective for downstream applications.

We work with structured and unstructured data sources, applying both automated enrichment tools and human expert review to ensure accuracy and relevance.

  • Entity extraction and knowledge graph linking
  • Geolocation tagging and address standardization
  • Product catalogue enrichment (categories, attributes, descriptions)
  • Cross-referencing with public and proprietary data sources
  • Taxonomy mapping and hierarchical categorization
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Data enrichment process adding structured attributes to raw datasets

Our Delivery Process

A transparent, milestone-driven process designed to keep you informed and in control at every stage.

1. Discovery & Scoping

We define requirements, quality benchmarks, timelines, and delivery formats together before any work begins.

2. Pilot & Validation

A small pilot run validates the annotation guidelines and quality approach before full production begins.

3. Production & QA

Full-scale production with continuous quality monitoring, inter-annotator agreement checks, and milestone reviews.

4. Delivery & Iteration

Structured delivery in your preferred format, followed by a review cycle and any required iterations.

Ready to Get Started?

Tell us about your data project and we'll put together a tailored proposal for you.

Request a Proposal