SERVICES
AI training data, end to end
From raw data collection to human feedback and evaluation — delivered by trained multilingual teams under rigorous QA.
RLHF & Preference Ranking
Human preference data is the backbone of aligned AI. Our contributors compare, rank, and rate model responses against detailed rubrics — producing clean preference signals your team can train on with confidence.
What's included
- Pairwise & multi-response ranking
- Response rating on custom rubrics
- Rubric and guideline co-development
- Inter-annotator agreement tracking
- Red-team style adversarial prompting (on request)
SFT Data Creation
Supervised fine-tuning is only as good as its examples. We write and curate instruction–response pairs, multi-turn dialogues, and domain-specific demonstrations in Bengali, Hindi, and English.
What's included
- Prompt writing & response drafting
- Multi-turn dialogue authoring
- Domain-specialized content (education, e-commerce, support)
- Style & persona-consistent writing
- Native-language localization of English datasets
Speech & Audio Data
We operate one of the region's most accessible native-speaker networks for Bengali and Hindi voice data — with English coverage available. Scripted or spontaneous, studio-clean or real-world conditions.
What's included
- Scripted & conversational voice recording
- Verified speaker demographics (age, gender, dialect)
- Transcription & time-aligned annotation
- Audio QA (SNR checks, clipping, mislabels)
- Custom collection protocols to your spec
Text Collection & Annotation
Custom text datasets collected and labeled to your taxonomy — from sentiment and intent classification to named entities and content moderation labels.
What's included
- Custom corpus collection
- Classification & sentiment labeling
- NER and span annotation
- Content moderation & safety labeling
- Bengali/Hindi linguistic annotation by native speakers
Data Validation & QA
Already have data? We audit and repair it. Every Quantore project also passes through our own two-stage review: peer review by senior contributors, then a leadership-level acceptance check against your spec.
What's included
- Independent dataset audits
- Two-stage internal review on all projects
- Gold-set benchmarking & agreement metrics
- Error taxonomy reporting
- Re-work included until acceptance criteria are met
Model Evaluation
Structured human evaluation that tells you how your model actually performs — for quality, helpfulness, safety, and cultural/linguistic correctness in South Asian languages.
What's included
- Side-by-side model comparisons
- Rubric-based single-response scoring
- Safety & policy compliance review
- Localization quality assessment
- Actionable summary reporting
Let's build your dataset.
Tell us what your model needs — get a scoped proposal within 48 hours.