No cycles wasted training on data that never should have been in the set.
How Coremantle works
Gold standard Indic data intelligence, with market-leading accuracy.
Coremantle puts technology at the centre of data operations, turning sourcing, annotation and human expertise into one quality-controlled system. We delivered 9.4% WER, 50% more accurate than the nearest benchmarked competitor.
How we ensure quality
Higher-quality data. More efficient training. Better-performing models.
100 HRS RAW DATA
01 · PRECISION SOURCING
02 · TECH-ENFORCED QC
03 · EXPERT COMMUNITY
04 · MODEL-READY DATA
LESS WASTE. MORE TRAINABLE DATA.
RAW & NOISY FILTERING & VALIDATION CLEAN & ENRICHED
01 · Precision sourcing
The hardest data to find. The right data to train on.
- Filter before ingestion so junk never enters the pipeline.
- Source the hardest data across dialects, accents, code-mix and real-world speech.
- Built to the model need by language, geography, domain and use case.
- More trainable yield with less rejection, rework and waste.
02 · Tech-enforced QC
The tech layer that makes quality non-negotiable.
- Guidelines enforced in-platform so quality does not depend on individual judgement alone.
- Automated QC at every step catches formatting, tagging, duplication and other preventable errors early.
- Indic-native tooling handles code-mix, language-specific input and real-world speech complexity.
- 2x throughput per annotator by removing repetitive human error before expert review.
03 · Our community
Our community of qualified linguistic workforce.
- Entry is earned through training, assessment and qualification.
- Native linguistic depth captures dialects, accents, code-mix and cultural context.
- Top performers become QC so proven experts protect output quality.
- Performance compounds quality through individual measurement, feedback and tiered progression.
04 · Model ready data
Ready for training. Built for production.
- Plug straight into training with verified, structured data.
- 9.4% WER on our 500-hour benchmark.
- >95% quality. Verified data flows straight into your training stack and the Coremantle Data Intelligence Layer with 2× throughput compared to industry.
Chapter 02 — Activate · Train · Deploy
EnterpriseYour business
BFSI · HealthTech · Logistics · eComm · Legal · AgriTech
→
Agentic AI layerRoutes · Decides · Responds
Only as good as the models underneath it
model-ready data ↓
Coremantle data intelligence layer← from chapter 01 · model-ready data
B1Model-ready data
B2Annotate & verify
B3Train custom model
B4Custom ASR · SLM · TTS
Verified data flows straight into your training stack — from model-ready data to production AI.
9.4%WER · 500h benchmark
>95%Dataset quality
2×Throughput
Why it pays off
The downstream advantage of model-ready data.
Clean source data means fewer errors baked into the model from day one.
Every batch is model-ready, not a starting point for more cleanup.
Data, graded
Two grades. Both trainable on day one.
Ready for production AI
For big tech, sovereign AI and voice AI builders. Code-mixing, diarization, timestamps, sentiment and precise labels, all included.
Code-mixingDiarizationTimestampsSentiment
Tuned to your vertical
Everything in Frontier grade, reviewed by a subject-matter expert in your domain — healthcare, legal, finance or beyond.
SME-reviewedDomain-specificSemantic enrichment
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See the quality before you train on it.
Save compute, reduce wasted runs, and train better models with cleaner data.