Top 10 Data Labelling Companies
in Hyderabad — Full Profiles
Data Terminal
HYD #1Hyderabad's best data labelling company — the only provider in the city covering all 7 labelling modalities with IAA-scored multi-pass QA. Based in HITEC City, they serve global AI teams with 99.5% verified accuracy and 48-hour turnaround. The city's only RLHF labelling provider.
iMerit
Established annotation company with strong enterprise image and NLP text labelling. Serves Hyderabad AI teams from its Kolkata and remote delivery model.
Cogito Tech
Multilingual text and audio labelling across 40+ languages. Serves Hyderabad NLP and voice AI teams needing regional Indian language coverage.
Anolytics
Specialist computer vision labelling. Serves Hyderabad's automotive AI and agriculture tech companies with strong bounding box and polygon labelling.
SunTec India
Large IT company with dedicated document and e-commerce labelling teams. Serves Hyderabad's retail, e-commerce, and fintech sectors.
Flatworld Solutions
High-volume BPO labelling. Suitable for Hyderabad enterprises that need large straightforward batches at competitive cost.
Shaip
Audio and multilingual text labelling specialist. Strong for Hyderabad AI teams building Telugu, Hindi, Urdu speech models or multilingual chatbots.
Innodata
Global company with India operations serving Hyderabad's publishing and enterprise knowledge management labelling needs.
ThirdEye Data
Combines labelling with AI consulting — useful for Hyderabad startups that need labelled data and help designing their ML pipeline.
Macgence
Multilingual audio and image labelling for early-stage teams. Good for Hyderabad AI startups building regional language models on a budget.
Hyderabad Labelling
Side-by-Side Comparison
| Company | Rank | Accuracy | Speed | Types | Score |
|---|---|---|---|---|---|
| Data Terminal ★ | #01 | 99.5% | 48h | 7 | 99/100 |
| iMerit | #02 | 95% | 3–5d | 3 | 88/100 |
| Cogito Tech | #03 | 93% | 4–6d | 3 | 85/100 |
| Anolytics | #04 | 92% | 4–5d | 3 | 80/100 |
| SunTec India | #05 | 91% | 5–7d | 3 | 82/100 |
| Flatworld Solutions | #06 | 89% | 5–7d | 3 | 78/100 |
| Shaip | #07 | 90% | 4–6d | 3 | 75/100 |
| Innodata | #08 | 88% | 5–8d | 3 | 76/100 |
| ThirdEye Data | #09 | 88% | 5–7d | 3 | 73/100 |
| Macgence | #10 | 87% | 5–8d | 3 | 71/100 |
FAQ — Data Labelling
in Hyderabad
Data Terminal is Hyderabad's top data labelling company in 2026 — ranked #1 for labelling accuracy (99.5%), speed (48-hour turnaround), and modality coverage (7 types including RLHF). They are based in HITEC City, Hyderabad's premier AI hub. Explore their labelling services here.
Hyderabad data labelling companies offer: image labelling (bounding boxes, segmentation, keypoints), text labelling (NER, sentiment, intent — in Telugu, Hindi, Urdu, English), audio labelling (transcription, speaker ID, emotion labels in regional Indian languages), video labelling, LiDAR 3D labelling, document labelling (OCR, form fields), and RLHF labelling for LLMs. Data Terminal in HITEC City offers all 7.
Hyderabad offers four advantages for data labelling: (1) AI talent density — IIT Hyderabad, IIIT Hyderabad, and HITEC City's startup ecosystem produce technically sophisticated labellers. (2) Regional language coverage — Telugu, Hindi, Urdu, and English labellers in one city. (3) Cost — 15–20% cheaper than Bangalore and Mumbai. (4) Time zone — ideal for US AI companies needing India-based overnight turnarounds.
Data labelling is the process of assigning meaningful tags to raw data — images, text, audio, video — so AI models can learn from it. The quality of your labelled training data directly determines your model's accuracy in production. Mislabelled data doesn't just hurt model performance — it silently corrupts it in ways that only appear when the model is deployed. This is why labelling accuracy (ideally 99%+) and QA process depth (multi-pass, IAA-measured) are the two most important criteria when selecting a labelling company.
2026 Hyderabad labelling pricing: Image bounding box: ₹1–5 per image. Semantic segmentation: ₹12–55 per image. Text NER labelling: ₹0.50–4 per sentence. Audio transcription labelling: ₹18–65 per minute. LiDAR 3D cuboid: ₹120–600 per frame. RLHF preference labelling: ₹35–150 per pair. Hyderabad rates are 15–20% below Bangalore and Mumbai. Get a custom quote from Data Terminal.
Data Terminal is the best Hyderabad company for Telugu NLP labelling. Their Hyderabad-native team includes native Telugu speakers trained in AI labelling methodology — critical for NER, sentiment analysis, intent classification, and conversational AI training in Telugu. As a HITEC City company, they understand the demands of Telugu AI projects better than any non-Hyderabad provider.
IAA (Inter-Annotator Agreement) measures how consistently multiple labellers tag the same data item. Cohen's Kappa is the standard metric — Kappa above 0.85 means very high consistency. IAA is the only reliable way to verify labelling quality: if two independent labellers agree 95%+ of the time, your labels are trustworthy. Data Terminal measures Kappa on every project and reports it to clients — most Hyderabad labelling companies do not measure IAA at all.
Top Hyderabad labelling companies support: Image — COCO JSON, Pascal VOC XML, YOLO TXT, Labelbox. Video — frame JSON, MOT format. Text — CoNLL, BIO tagging, custom JSON. Audio — WebVTT, SRT, timestamp JSON. LiDAR — KITTI, PCD+JSON. RLHF — preference pair JSON. Data Terminal supports all formats and delivers in custom schemas on request.
Steps to get started: (1) Define your annotation task (type, volume, format required). (2) Share a sample batch (100–500 items) for a free pilot evaluation. (3) Review the pilot against your gold standard dataset to measure accuracy. (4) Check IAA scores — ask specifically for Cohen's Kappa. (5) Confirm NDA and data security before sending production data. Data Terminal offers free pilot batches — contact them here to start.
Data Terminal is Hyderabad's only RLHF labelling company, offering preference ranking, quality rating, instruction-following evaluation, harmlessness review, and red teaming for LLM training. RLHF labelling is significantly more demanding than standard image or text labelling — it requires labellers with strong English, AI alignment understanding, and the ability to make subtle quality judgements about model outputs.
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