01
Your data exists. It just isn’t AI-ready.
Enterprise data is scattered across calls, chats, documents, and systems, often noisy, unstructured, and missing the context AI needs.
From enterprise data to the readiness gap
Training-ready data intelligence for enterprise
Your AI is only as ready as its training data.
Coremantle delivers production-grade training data designed to improve model performance, reduce errors, and accelerate the path from experimentation to deployment.
The data infrastructure gap
The world’s AI ambition is outrunning its data.
Billions of people use languages that today’s models barely hear. The problem grows from scarcity into complexity, wasted compute, and compliance risk.
02
AI learns from the wrong signals.
Poor transcription, irrelevant information, duplicates, and inaccurate labels can teach models the wrong patterns.
Wrong signals, wasted compute
03
Domain complexity gets lost.
Accents, code-switching, industry terminology, customer intent, and edge cases are what make enterprise data difficult to prepare well.
One conversation. Many layers.
04
Bad data limits what your AI can automate.
When models struggle to understand intent or execute real workflows, enterprises keep humans in the loop, driving up costs and limiting agent automation.
The automation ceiling
The missing infrastructure
So, we built the data infrastructure AI has been missing.
Using real natural conversational data, we turn weak model performance into production-ready accuracy.
In our benchmark, accuracy improved from 23% to 91% with just 500 hours of customer call data.
Model benchmark
Quality by design
We engineered quality into every layer.
From compliant sourcing to a tech-first platform and a curated community of native experts, every layer is designed to eliminate error before it reaches the model.
- 04
Model-ready output
Every dataset verified, certified, and benchmarked before delivery.
- 03
Curated community
Native experts vetted for language, dialect, and domain — not crowd workers.
- 02
Tech-first platform
75% of the pipeline is already automated versus ~30% industry standard, including quality enforcement built directly into every stage.
- 01
Raw data sourcing
100% of raw data sources are guaranteed to increase model performance — clear sourcing, filtration before ingestion, DPDP-compliant consent.
EnterpriseYour business
BFSI · HealthTech · Logistics · eComm · Legal · AgriTech
→
Agentic AI layerRoutes · Decides · Responds
Only as good as the models underneath it
←
API vendorsGeneric ASR · LLM · TTS
⚠ Fails for Indian context
live call data ↓⇅ replaces generic APIs
Coremantle data intelligence layer
Your call data
Annotate & verify
Train custom model
Custom ASR · SLM · TTS
The result is verified, model-ready data built for production AI.
Where language complexity matters
Built for the industries where context is critical.
Banking and financial services
Train AI on real financial conversations, terminology, accents, and customer intent.
Healthcare
Build language models that understand clinical context, patient speech, and regional variation.
Legal
Prepare AI for complex legal language, domain vocabulary, and multilingual documentation.
eCommerce
Improve search, support, and conversational AI across the languages customers actually use.
Logistics
Train voice and agentic systems for high-volume, multilingual operations in the real world.
AgriTech
Make AI understand farmers across regional languages, dialects, and agriculture-specific vocabulary.
Get started
Choose how you want to build.
Get training-ready data and let us build the agentic solution, or take the data and build it your way.