AI & scientific computing
ONNX development & integration
Move compatible models between training and inference environments through a portable representation.
Intelligence with connected context
01 / The detail
What we can build
Move compatible models between training and inference environments through a portable representation.
- Model export
- Runtime integration
- Parity testing
02 / The detail
Illustrative use case
A model trained in one framework and deployed in a separate inference runtime.
03 / The detail
Decisions that matter
Conversion can change supported operations or numerical behavior. Compare outputs and performance with the original model.
04 / The detail
From scope to a working release
Start with representative data and a measurable task. Compare against a simple baseline, reserve evaluation samples, document failure modes, and validate latency, operating cost and privacy before connecting outputs to business actions.
- A scoped workflow and explicit acceptance criteria
- A tested implementation with documented dependencies
- Deployment, recovery and maintenance responsibilities agreed before handover
Across India
ONNX development for teams in every major Indian city.
We work remotely with businesses across India, in Indian working hours, with calls, shared boards and scheduled reviews. Teams we can support include:
- ONNX development in Mumbai
- ONNX development in Delhi NCR
- ONNX development in Bengaluru
- ONNX development in Hyderabad
- ONNX development in Chennai
- ONNX development in Pune
- ONNX development in Ahmedabad
- ONNX development in Surat
- ONNX development in Vadodara
- ONNX development in Rajkot
- ONNX development in Kolkata
- ONNX development in Jaipur
- ONNX development in Indore
- ONNX development in Nagpur
- ONNX development in Lucknow
- ONNX development in Chandigarh
- ONNX development in Kochi
- ONNX development in Coimbatore
- ONNX development in Noida
- ONNX development in Gurugram
- ONNX development in Vapi
- ONNX development in Silvassa
- ONNX development in Daman
- ONNX development in Umargam
Questions, answered
Before we begin.
When is ONNX a useful fit?
Move compatible models between training and inference environments through a portable representation. Start by comparing the required workflow with your existing systems. A model trained in one framework and deployed in a separate inference runtime.
What should we resolve before implementation?
Conversion can change supported operations or numerical behavior. Compare outputs and performance with the original model.
Do you take on ONNX projects from other cities in India?
Yes. We work remotely with teams in Mumbai, Delhi NCR, Bengaluru, Hyderabad, Chennai, Pune, Ahmedabad, Surat and other cities across India, with calls, shared boards and scheduled reviews in Indian working hours.
How do we begin a project?
Share the workflow, intended users, existing systems and any release constraints. Discovery establishes scope, dependencies and acceptance criteria; estimates follow that assessment rather than a fixed promise before the requirements are known.
Start with the problem.
Build the right solution.
Bring your idea, workflow or existing application. We’ll help define a practical next step.