---
title: "Computer Vision Development | India-Based AI Engineers"
description: "Object detection, inspection, OCR, and visual quality control built by an India team for US companies. From prototype to deployed edge or cloud vision."
image: "https://foundrysoft.co/api/og?type=page&title=Computer+Vision+Development+%7C+India-Based+AI+Engineers&st=Object+detection%2C+inspection%2C+OCR%2C+and+visual+quality+control+built+by+an+India+team+for+US+companies.+From+prototype+to+deployed+edge+or+c%E2%80%A6"
url: "https://foundrysoft.co/services/computer-vision-development-india"
---

Computer Vision · Built in India for US companies

# Computer vision development

We build computer vision systems for US companies: object detection, visual inspection, quality control, and image understanding, deployed to the cloud or onto edge devices. From a labeled dataset to a model running in production.

Book a 30-min scoping call [See our work](https://foundrysoft.co/work)

No sales script. You talk to the engineers who'd build it.

9+ hrs

Timezone overlap

Our team works a shifted day so you get real-time standups and same-day turnarounds in your time zone, not next-morning replies.

100%

You own the IP

Every line of code, model weight, and prompt is yours from day one. NDAs and clean IP assignment are standard, not an upsell.

Senior

No juniors hidden on the bill

You work directly with the engineers building your system. No account managers sitting between you and the people writing code.

Weeks

To first deployment

We move from scoping to a working system in production in weeks. Most engagements ship something usable inside the first month.

## What we build

Concrete systems we ship, tuned to your data and your stack.

### Detection & tracking

Find, count, and track objects in images and video streams in real time.

### Visual inspection

Spot defects and quality issues faster and more consistently than manual checks.

### Image understanding

Multimodal models that describe, classify, and answer questions about images.

### Edge deployment

Models optimized to run on-device where latency or connectivity rules out the cloud.

## How we work

01

### Scope & evals

We pin down what success means and build the evaluation set before writing the feature, so quality is measured, not guessed.

02

### Build in the open

Weekly demos against real data. You see progress every week and can change direction before it gets expensive.

03

### Ship & instrument

We deploy with logging, cost tracking, and guardrails in place, then tune against production traffic.

04

### Hand off or stay

Take the keys with full docs, or keep us on for iteration. Either way you're never locked in.

## Questions, answered

### Do we need a labeled dataset already?

+

It helps, but we can start from raw data and handle labeling, or use multimodal models that need far less training data than classic vision pipelines.

### Can the model run on edge hardware?

+

Yes. We optimize and quantize models to run on cameras, Jetson devices, and other edge hardware when cloud latency isn't an option.

### How accurate will it be?

+

We benchmark against a held-out test set and report real precision and recall, then iterate. You get measured performance, not a marketing number.

### Can you combine vision with language models?

+

Yes. Multimodal systems that both see and reason are a sweet spot, for example reading a document image and answering questions about it.

## Let's scope your build.

Tell us what you're trying to ship. We'll tell you honestly whether AI is the right tool and what it would take.

Start the conversation

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