Why South Indian Languages Break Most ASR Models
Code-switching, dialect density, and what general-purpose models consistently miss.
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Built in Tamil Nadu, for Global AI
High-Precision AI Data Engineering
Accurate, culturally-aware, AI-ready datasets engineered for high-stakes industries — with a rigorous, human-verified pipeline across Tamil, Telugu, Kannada, and Malayalam.
4South Languages
48hDelivery SLA
100%DPDP Compliant
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Get early access to our dataset catalog, pre-trained audio models, and pilot batches.
Pipeline Engineering
The robust, high-quality mechanism we use to build your data — grouped into three engineered stages.
01
Data Collection & Pre-processing
Native-speaker speech collection across regional dialects, plus cleaning, slicing, noise removal, and normalization — so raw input meets technical spec before annotation begins.
Speech CollectionPre-processingNormalization
02
High-Precision Annotation
Expert labeling and ASR-ready verbatim transcription with phonetic markers and timestamps — comprehensive coverage from entity tagging to clean transcripts, reviewed by native speakers.
Data AnnotationIndic Transcription
03
Validation & RLHF
Our gold-standard layer: human-preference alignment (RLHF), model evaluation, and multi-stage QA. We don't just label data — we refine it through human-in-the-loop cycles for AI safety and factual accuracy.
RLHFLLM EvaluationMulti-Stage QA
See how our pipeline powers accuracy for high-stakes industries ↓
Supported Vernaculars
Select a language below to explore our target regional dialects, local phonetic nuances, and simulated speech waveforms.
Tap a southern state to explore its language, dialects & culture
Tamil (தமிழ்)
Deep coverage of Tamil's regional and urban speech, with strong handling of agrarian vocabulary and natural Tanglish code-switching patterns.
Ancient Dravidian temples, Bharatanatyam, and the Pongal harvest festival — with deep Kongu agrarian roots.
Verbatim Spoken Sample
"எங்க போயிட்டு வர்றீங்க? அங்கன வேலை முடிஞ்சுதா?"
"Enga poyittu varreenga? Angana velai mudinjutha?"
0:00
English Context Meaning
"Where are you coming from? Did the work finish over there?"
AI Data Workflow Architecture
We translate raw regional voice and text into structured, validated data payloads using a rigorous 6-step process — with Human-Preference Alignment (RLHF) and sectoral alignment built in as standard.
Step 01
Data Collection
Sourcing acoustic files and textual queries from native populations in target geographies.
Label StudioCVATWhisper
PraatPythonAWS Cloud
Specialized Domains
Tailored datasets for high-stakes industries where accuracy is non-negotiable.
Healthcare
Clinical-grade accuracy for medical transcription, terminology, and patient-voice data.
Legal
Verbatim transcriptions and document data with strict fidelity and confidentiality.
Manufacturing
Equipment logs, shop-floor speech, and technical documentation in regional languages.
Finance & Banking
Conversational and KYC data for vernacular banking and e-governance assistants.
Government & Public Sector
Citizen-service and public-data localization across South Indian languages.
Agriculture
Agrarian vocabulary and farmer-voice data — a core strength of our regional coverage.
Trust & Compliance
Built for enterprise and government procurement — secure, confidential, and accountable by default.
DPDP Act 2023 Compliant
Our pipeline follows India's Digital Personal Data Protection Act, 2023.
NDA & Confidentiality
Every engagement runs under NDA; client data is never reused across projects.
Secure Data Handling
Encryption in transit and at rest, role-based access, and full audit trails.
Data Residency in India
Processing and storage kept within India unless you specify otherwise.
Multi-Stage QA Sign-off
Guideline creation, dual review, adjudication, and final approval on every batch.
ISO 27001 on Our Roadmap
Audit-ready practices today, with formal ISO 27001 certification planned.
From the Lab
Insights on South Indian language data, AI quality, and building Indic datasets that work.
Inside Our Multi-Stage QA Pipeline
How guideline design, dual review, and adjudication keep annotation accuracy high.
Visit the blog →RLHF for Indic LLMs: A Practical Primer
What human-preference alignment really looks like for vernacular language models.
Visit the blog →Building an Indic AI model? Let's talk data.
Tell us your language, modality, and volume — we'll scope a pilot batch within 48 hours.