AI data
services
AI data services are the work of turning raw material into training-ready datasets — collection, annotation, validation and formatting. Lifewood delivers that end to end, from multi-language collection and annotation to model training and generative AI content. Leveraging our global workforce, industrialized methodology, and proprietary LiFT platform.
Data Validation
The goal is to create data that is consistent, accurate and complete, preventing data loss or errors in transfer, code or configuration.
We verify that data conforms to predefined standards, rules or constraints, ensuring the information is trustworthy and fit for its intended purpose.
Data Collection
Lifewood delivers multi-modal data collection across text, audio, image, and video, supported by advanced workflows for categorization, labeling, tagging, transcription, sentiment analysis, and subtitle generation.
Our scalable processes ensure accuracy and cultural nuance across 30+ languages and regions.
Data Acquisition
End-to-end data acquisition solutions — curation, processing, and managed large-scale diverse datasets built for enterprise AI systems.
Data Curation
We sift, select and index data to ensure reliability, accessibility and ease of classification. Data can be curated to support business decisions, academic research, genealogies, scientific research and more.
Data Annotation
High quality annotation services for vision, speech and language processing to accelerate model development. In the age of AI, data is the fuel for all analytic and machine learning.
"Lifewood provides high quality annotation services for a wide range of mediums including text, image, audio and video for both computer vision and natural language processing."
The LiFT platform
LiFT is Lifewood's proprietary delivery platform for AI data services. It unifies multi-language collection, annotation, validation, and AI-generated content production under a single industrialized workflow — the operating layer behind every Lifewood program across 50+ languages and 40+ delivery centers.
AI Data Services FAQ
AI data annotation is the process of labeling raw data — text, images, audio, video, LiDAR point clouds — with structured tags that machine learning models can learn from. Lifewood operates AI data annotation across 50+ languages and all major modalities with a 95%+ accuracy SLA.
Lifewood enforces accuracy through a dual-layer human-in-the-loop QA process: a first-pass annotator labels the data, a second-pass auditor independently reviews a statistical sample, and disagreements are arbitrated against per-program calibration sets. Below-threshold batches are reworked at Lifewood's cost.
Lifewood annotates text (intent, NER, sentiment, RLHF ranking), image (2D/3D bounding box, segmentation, keypoint, OCR), audio (transcription, phoneme, sentiment, ASR), video (temporal labeling, action recognition), and LiDAR / radar (3D detection, segmentation, fusion alignment).
Pilots typically launch within 1 week of contract execution. Full production ramp to several thousand annotation hours per week takes 2 to 4 weeks depending on language mix, modality, and accuracy SLA. Multi-year umbrella frameworks are also common for ongoing programs.
Yes. Lifewood specifically supports low-resource languages through region-native annotators across our delivery centers in the Philippines, Bangladesh, Africa, and Southeast Asia. Coverage spans 50+ languages including underrepresented dialects. See our dedicated low-resource speech data page for details.
Human-in-the-loop (HITL) annotation pairs human reviewers with automated tooling to ensure both speed and accuracy. AI-assisted pre-labels are corrected by human annotators, then validated by a second-pass auditor. HITL is the standard at Lifewood for any program where final-model accuracy matters.
Related services & resources
- Enterprise LLM Training DataInstruction, preference, and domain corpora built for fine-tuning.
- Multilingual Data CollectionNative-speaker collection across 50+ languages and dialects.
- AI Data ValidationIndependent dual-layer QA against a contractual 95%+ accuracy SLA.
- Autonomous Driving AnnotationLiDAR, camera, and radar perception labeling for AV stacks.
- Low-Resource Speech DataSpeech corpora for languages with little or no public training data.
- Type A — Data ServicingCore annotation and enrichment across text, image, audio, and video.
- QA ProcessThe dual-layer human-in-the-loop review behind every delivery.
- Delivery MethodologyThe six-stage pipeline from scoping through post-delivery audit.
- Hyperscale Enterprise Data Case StudyEnterprise-scale data servicing and quality operations.
- AI Glossary30+ defined terms across AEO, GEO, AIGC, and data operations.
- FAQDirect answers to the questions buyers and answer engines ask most.
- ContactScope a program, request a sample, or book a technical call.