YNTR
AI models, inference, agentic systems and model-related research under DoubleSlit.
What YNTR explores
Models
Training and evaluating models for defined tasks.
Inference
Running models efficiently, in the cloud or at the edge.
Agentic systems
Systems that plan and act within defined permissions.
Deep-tech themes
Illustration of themes explored under YNTR.
From understanding to action
The questions YNTR research aims to answer. These are research capabilities, not product claims.
Understanding
What is happening?
Detection
What is unusual?
Prediction
What may happen next?
Recommendation
What should we consider doing?
Action
What can be automated, with accountability?
Where models can run
Cloud, edge, private or hybrid, chosen per application.
- Edge AI: run intelligence close to where data is generated.
- Private AI: customer-controlled environments.
- Hybrid architectures with a defined boundary for what leaves the site.
- India-first goals: data residency, local intelligence and Indian-language capability, scoped per project.
Governance for every model, including oversight, data use and transparency, is set out in Responsible AI.
Status
YNTR does not manage identity or hold a twin registry; those belong to Helix. Each model or project page should show its maturity label and whether it runs in any product.