Custom text data collection for NLP & LLM training
Custom, consent-compliant text datasets for NLP and LLM training — receipts, clinical notes, prompts, RLHF and fine-tuning data in 150+ languages.
What is text data collection?
Text data collection is the gathering, generation, transcription and licensing of written-language data used to train and fine-tune NLP and large language models — with consent, clear rights and known provenance, unlike scraped web text.
How our expertise support you:
Modern language models need more than volume. They need text that matches the task, the domain and the language mix of the real users a model will serve — labelled consistently and delivered in a training-ready format. Shaip’s text data collection services cover the full range: from large pretraining corpora to small, high-precision fine-tuning and preference sets.
Text data types we collect
Shaip’s text data collection services span document, conversational and specialised text — collected or transcribed to your schema and delivered in JSONL, CoNLL, CSV or your pipeline format.
Receipts & invoices
OCR, document AI and expense automation. Image + JSON labels, 150+ languages.
Clinical notes & physician dictation (EHR)
Healthcare NLP, medical coding and ASR. De-identified transcripts.
Identity & financial documents
IDP, KYC and document understanding. Image + structured labels.
Handwritten text
Handwriting recognition (HTR) and archives. Scans + transcriptions.
Chat & conversational logs
Chatbots, conversational AI and intent. Turn-structured text.
Prompts & responses
LLM SFT, instruction tuning and RAG. Prompt/response pairs in JSONL.
Preference / ranked responses
RLHF and model alignment. Ranked completions with rationale.
Domain corpora
Pretraining and domain adaptation. Cleaned, de-duplicated text.
NER, sentiment & intent sets
Classic NLP training. Token- or span-labelled text (CoNLL/JSON).
Text data, labelled or human-generated
Annotation for task-specific models and human-authored data for every stage of the LLM lifecycle — to your guidelines, with documented consent and provenance.
Annotate existing text
- Named-entity recognition Tag people, places, dates and domain terms in existing text.
- Intent & text classification Sort messages and documents into intents, topics or categories.
- Sentiment analysis Label the tone of text as positive, negative or neutral.
- Content moderation Flag unsafe, abusive or policy-violating text.
- Extractive summarization & QA labels Mark the key spans and answer passages within a document.
Create & rank new text
- Supervised fine-tuning Write instruction–response pairs that teach a model your task.
- RLHF & preference ranking Rank model responses to align it with human preferences.
- Prompt & response collection Author varied prompts and responses for tuning and RAG.
- Domain-specific corpora Curate in-domain text for pretraining or adaptation.
- Evaluation sets & red-teaming Build test and adversarial prompts to probe accuracy and safety.
Our Expertise
Text Data Collection Types that We Cover
The true value of Shaip cognitive text data collection services is that it gives organizations the key to unlock critical information found deep within unstructured text data. This unstructured data can include physician notes, personal property insurance claims, or banking records. A large amount of text data collection is essential in developing technologies that can understand human language. At Shaip, you get the full data collection stack when training models using documented sources are concerned. Our services cover a wide variety of text data collection services to build high-quality NLP datasets.
Receipt Data
Collection
Teach your intelligent eCommerce models to identify invoices with precision.
Our OCR technology and relevant identification techniques help you feed data pertaining to taxi receipts, internet bills, restaurant bills, shopping invoices, and multi-lingual receipts into the machines for training them holistically
Ticket Dataset
Collection
Remodel your digital travel assistant with
impactful insights
Ensure that your custom AI model can identify railway, cruise, airline, bus, and other tickets to perfection with ample text datasets for machine learning and OCR insights being fed into the same.
EHR Data & Physician Dictation Transcripts
Train healthcare models proactively to improve clinical accuracy.
Our text data collection solutions accommodate medical data sets and transcripts, thereby allowing you to construct inventive digital healthcare setups that can store clinical insights, manage workflow, and automate medical transcription.
Document Dataset
Collection
Prep Digital RTOs, Payment Banks, and Professional setups, intelligently
We help you set up models that serve a professional purpose by letting them identify documents. Our coverage extends across credit cards, property documents, driving licenses, visa datasets, and more
Intent Variation
Dataset
Design enlightened NLP systems that can identify Intent.
Now train machines to identify the intent of your textual inputs. Shaip lets you in on intent recognition and intent classification to detect emotions from sentence structuring and worded order.
Handwritten Data Transcription
AI Text detection and recognition models at your fingertips.
Transcribe a wide range of historical documents or even handwritten notes using handwritten data transcription. Plus, our granular training approach lets your model recognize the structure, layout, and text
Chatbot Training
Data
Deploy interactive chatbots for a more professional appearance
We have Chatbot training datasets at our disposal to help you develop some of the more interactive programs for your professional setup. With our text message data collection and vertical-based services, it becomes easier for chatbots to respond organically to textual inputs.
OCR
Training
Add a visual element to textually-powered AI models
Our services cover OCR (optical character recognition) as a standalone service, allowing you to intelligently recognize words, characters, insights from scanned photographs, and more, with reliable datasets to feed the machine with.
Success Stories
10,000 Pages of Oncology Data for NLP Training
Shaip delivered de-identified, high-quality oncology records to help train NLP models for clinical research and healthcare applications.
Problem: Process complex oncology records while protecting patient privacy & accurately capturing clinical entities, relationships, and negation.
Solution: HIPAA-compliant de-identification & expert annotation across 10k pages of oncology records, covering clinical entities, relationships.
Result: A high-quality, de-identified dataset supporting oncology NLP model development and healthcare research.
99% Accuracy for OCR Text Detection & Transcription
Shaip created production-ready OCR training data across documents, handwriting, signage, receipts, license plates, and other real-world text sources.
Problem: Accurately detect and transcribe text across different formats, orientations, languages, and challenging visual conditions.
Solution: Word-level bounding boxes, character-level transcription, 5 attribute layers, and dual QA across 10+ text source types.
Result: A production-ready OCR dataset achieving a 99% accuracy threshold for document intelligence and real-world text recognition.
How Shaip collects text data
A six-step, QA-gated workflow from scope to delivery.
- Scope & schema. Define use case, languages, domains, label schema, format and acceptance criteria.
- Sourcing & consent. Recruit vetted contributors or license source text; secure consent and usage rights; document provenance.
- Collection & transcription. Gather, generate or transcribe text to specification, with PII handling and de-identification where required.
- Annotation & labelling. Apply NER, intent, sentiment, preference or instruction labels against written guidelines.
- Multi-tier QA. Six Sigma stage-gate review with inter-annotator agreement and sampling to your accuracy threshold [VERIFY].
- Delivery & iteration. Ship in JSONL, CoNLL, CSV or your pipeline format; iterate on feedback and scale.
Why teams choose Shaip for text data
Data Collection Capabilities
Create, curate, and collect custom-built datasets (text, speech, image, video) from across the globe based on custom guidelines.
Flexible Global Workforce
Leverage 10,000+In-house global workforce and 500K+ Crowd-scale credentialed contributors. Real-time workforce capacity and efficiency.
Quality
Our proprietary platform & skilled workforce use multiple quality control methods to meet or exceed quality standards.
Diverse, Accurate & Fast
Our process streamlines, the collection process through easier task distribution, & data capture directly from the app & web.
Data Security
Maintain complete data confidentiality by making privacy our priority. We ensure data formats are policy controlled and preserved.
End-to-End Annotation
Every collected dataset can be annotated, labeled, transcribed, and validated in the same workflow, delivering model-ready training data.
Security & Compliance
Services Offered
Expert text data collection isn’t all-hands-on-deck for comprehensive AI setups. At Shaip, you can even consider the following services to make models way more widespread than usual:
Audio Data Collection Services
We make it easier for you to feed the models with voice data to help them explore the perks of Natural Language Processing in a more balanced way
Image Data Collection Services
Make sure that your computer vision model identifies every image accurately, to seamlessly train next-gen AI models of the future
Video Data Collection Services
Now focus on computer vision along with NLP for training your models to identify objects, individuals, deterrents, and other visual elements to perfection
Want to build your own data set?
Contact us now to let go of your text training data collection worries.
Frequently Asked Questions (FAQ)
1. What is text data collection in machine learning?
It is the sourcing, creation, transcription and licensing of written-language data — documents, chats, prompts, transcripts and labels — used to train and fine-tune NLP and large language models with known provenance and consent.
2. What types of text data can Shaip collect?
Receipts and invoices, clinical notes and physician dictation, identity and financial documents, handwritten text, chat and conversational logs, prompt–response pairs, RLHF preference data, domain corpora, and NER, sentiment, intent, QA and summarization sets.
3. Can you collect data to train or fine-tune an LLM?
Yes. Shaip provides pretraining corpora, SFT instruction–response data, RLHF preference data, and evaluation and red-teaming sets, formatted for common fine-tuning frameworks.
4. How is text data collected and kept high quality?
Through scoping, consent-secured sourcing, collection or transcription, annotation to written guidelines, and a multi-tier Six Sigma QA process with inter-annotator agreement checks.
5. How much does text data collection cost?
Cost depends on data type, language, volume, annotation complexity and QA level. Shaip scopes each project and can start with a pilot so you can validate quality before scaling.
6. Is the data licensed, consented and compliant?
Yes. Usage rights are secured and documented, contributor consent is captured, PII is de-identified or redacted, and delivery follows Shaip’s compliance framework — GDPR, HIPAA, SOC 2 Type II, ISO 27001.
7. Custom collection or off-the-shelf datasets — which do I need?
Off-the-shelf is fastest for generic tasks; custom collection fits specific domains, languages, schemas and licensing. Shaip offers both.
