AI development
AI development for production
Visiobyte is an AI development company in Rajkot, working with teams in India and abroad. We build computer vision, language, and prediction systems, then put them behind an API your product can call.
The problem
Most AI work stalls after a notebook. The model looks fine on a sample set, then latency, bad inputs, and missing ownership keep it off the production path. The business still does the job by hand.
We start from the decision the model has to support: flag a defect, score a lead, classify an image, or draft a summary. Then we measure accuracy, speed, and what happens when the input is wrong, and we ship the system that makes that decision.
What we deliver
Models fit to the job
Vision, language, and classical ML, trained and evaluated on your data with a metric the business can read.
APIs and product surfaces
Inference behind a stable API, or a small app your team logs into, so the model is part of the workflow.
Evaluation you can trust
Holdout sets, error review, and thresholds for when a person should take over.
Deployment on your cloud
Containers, queues, and storage on Azure or the stack you already run, with a path to scale inference.
How we work
01
Name the decision
We sit with the people who do the work and write down the input, the output, and what a wrong answer costs.
02
Check the data
We look at volume, labels, edge cases, and privacy limits before anyone trains a model.
03
Build and integrate
We train, evaluate, and connect the model to the system that will call it.
04
Run it
We deploy, watch latency and errors, and improve the model as new data arrives.
Questions
- What does Visiobyte build as an AI development company?
- Custom models, APIs, and products for computer vision, language, and prediction. The system is built to run in production, with a measured result your team can use.
- Where is Visiobyte based?
- Rajkot, Gujarat, India. We work with teams in India and with clients abroad.
- Do you deliver a model file or a system we can run?
- A system. That includes evaluation, an API or a small app, and deployment on Azure or the cloud you already use.
- How does an AI project start?
- We start from the decision the model has to support, then look at your data, what a wrong answer costs, and how the result should reach the people who use it.
Related work
A project in this line of work. The write-up covers the problem, what we built, and the result.