London-based Computer Vision engineers will design, train, validate, and deploy a bespoke object detection model — from research and data preprocessing through to cloud deployment and full API integration, with source code included.
I Will Build a Custom Object Detection Model for Your Application
A fully trained and validated custom object detection model with cloud deployment and API integration.
- Custom object detection model (images or video)
- Research, data preprocessing, model creation and fine-tuning
- Model validation, testing and performance monitoring
- Cloud deployment with REST API integration
- Full source code and model documentation delivered
- Unlimited revisions — IP belongs entirely to you
Everything in Starter plus expanded scope — ideal for multi-class or higher-complexity detection tasks requiring extended development time.
- All Starter deliverables included
- Extended development scope for more complex or multi-class detection tasks
- Broader framework selection across full supported model stack
- Deeper fine-tuning cycles with additional iteration rounds
- Cloud deployment and API integration at production scale
- Full source code, weights and comprehensive model documentation
Full-scale end-to-end delivery for large or mission-critical projects — maximum scope, edge and mobile deployment, and complete documentation.
- All Professional deliverables included
- Maximum project scope for complex, multi-stage or high-volume detection systems
- Deployment to cloud servers AND edge/mobile targets (Android, iOS, Raspberry Pi, OpenVINO)
- Custom pose estimation (pitch, yaw, roll) if required by your use case
- Full REST API development and server deployment
- Complete source code, model weights, inference scripts and thorough documentation
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Value Position
Framework Support
Deployment Targets
Domain Experience
Deliverable Scope
What You'll Receive
Full Description
Your business problem is unique. Off-the-shelf vision models rarely fit it. This service delivers a production-ready custom object detection model built specifically around your data, your environment, and your deployment target — so you receive something that actually works in the real world, not just on a benchmark.
Our London-based team of Computer Vision engineers holds qualifications spanning BSc Computer Science through to MSc and PhD in Computer Vision. We have built and shipped detection models across healthcare, agriculture, motorsport, security, energy, and consumer applications — covering everything from medical device reading and melanoma spot detection to traffic cone recognition, solar panel identification from drone imagery, and driver safety monitoring. Every model we deliver has gone through the same rigorous end-to-end process described below.
**What every package includes:**
Research — we review the literature and best-fit architectures for your specific detection task before writing a single line of code.
Data preprocessing — your raw images or video frames are cleaned, annotated-check, augmented and split into training, validation and test sets.
Model creation — we select and configure the optimal architecture from our supported framework stack (YOLOv5, PyTorch, TensorFlow Lite, ONNX, CoreML, TensorRT, TensorFlow.js, OpenVINO, TorchScript) based on your accuracy, speed and hardware requirements.
Validation and testing — models are evaluated against held-out data with full precision/recall/mAP reporting so you know exactly what performance to expect.
Performance monitoring and fine-tuning — we iterate until the model meets the agreed target metric before handoff.
Cloud deployment and API integration — the model is wrapped in a REST API and deployed to a cloud server (such as EC2) so it is immediately callable from your application.
Source code and model documentation — you receive everything: weights, training scripts, inference scripts, API code, and written documentation. All intellectual property belongs entirely to you.
**Deployment targets we support:** cloud servers, Android, iOS, Raspberry Pi, and other edge devices running OpenVINO or compatible runtimes.
**Who this is for:** product teams and startups building vision-powered features; enterprises automating visual inspection or monitoring; researchers needing a production-grade model rather than a research prototype; any organisation that has tried a generic model and found it falls short.
Please message us before placing your order so we can understand your dataset, targets, and timeline. We will confirm scope and any additional requirements in advance — no surprises mid-project.
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Compare Packages
| Feature | Starter | Professional | Enterprise |
|---|---|---|---|
| Delivery Time | 14 days | 21 days | 21 days |
| Revisions | unlimited | unlimited | unlimited |
| Custom object detection model (images or video) | ✓ | ✕ | ✕ |
| Research, data preprocessing, model creation and fine-tuning | ✓ | ✕ | ✕ |
| Model validation, testing and performance monitoring | ✓ | ✕ | ✕ |
| Cloud deployment with REST API integration | ✓ | ✕ | ✕ |
| Full source code and model documentation delivered | ✓ | ✕ | ✕ |
| Unlimited revisions — IP belongs entirely to you | ✓ | ✕ | ✕ |
| All Starter deliverables included | ✕ | ✓ | ✕ |
| Extended development scope for more complex or multi-class detection tasks | ✕ | ✓ | ✕ |
| Broader framework selection across full supported model stack | ✕ | ✓ | ✕ |
| Deeper fine-tuning cycles with additional iteration rounds | ✕ | ✓ | ✕ |
| Cloud deployment and API integration at production scale | ✕ | ✓ | ✕ |
| Full source code, weights and comprehensive model documentation | ✕ | ✓ | ✕ |
| All Professional deliverables included | ✕ | ✕ | ✓ |
| Maximum project scope for complex, multi-stage or high-volume detection systems | ✕ | ✕ | ✓ |
| Deployment to cloud servers AND edge/mobile targets (Android, iOS, Raspberry Pi, OpenVINO) | ✕ | ✕ | ✓ |
| Custom pose estimation (pitch, yaw, roll) if required by your use case | ✕ | ✕ | ✓ |
| Full REST API development and server deployment | ✕ | ✕ | ✓ |
| Complete source code, model weights, inference scripts and thorough documentation | ✕ | ✕ | ✓ |
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Build a Custom Object Detection Model for Your Application


Build a Custom Object Detection Model for Your Application

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Frequently Asked Questions
Yes, please — and we strongly encourage it. Every object detection project has unique requirements around dataset size, number of classes, target accuracy, and deployment environment. A brief conversation before you order lets us confirm scope, agree on timelines, and ensure there are no surprises during development. Simply send us a message describing your project and we will respond promptly.
Not necessarily. If you already have labelled data, we will use it directly. If you have unlabelled images or video, we handle data preprocessing as part of every package — including checking annotations, augmentation, and splitting data into training, validation and test sets. Please share as much detail as possible about your data when you first contact us.
We select the best-fit architecture for your specific task, accuracy requirements, and target hardware. Our supported stack includes YOLOv5, PyTorch, TensorFlow Lite, ONNX, CoreML, TensorRT, TensorFlow.js, OpenVINO and TorchScript. We will recommend the most appropriate option after discussing your project.
You do — entirely. All intellectual property, including the model weights, training scripts, inference code, API code and documentation, transfers to you on delivery. We retain no rights to anything we build for you.
It means we will keep iterating on the model — tuning hyperparameters, adjusting augmentation, refining the architecture — until it meets the performance targets agreed at the start of the project. Revisions are bounded by the agreed scope; changes that significantly expand the project (for example, adding entirely new object classes) may require a scope discussion.
Yes. We work with organisations of all sizes on both one-off deliveries and ongoing engagements. If your project is larger or more complex than a standard order, please message us first and we can discuss a structured approach, milestones and timelines that suit you.
Yes. We take responsibility for the full pipeline — from initial research and architecture selection, through data preparation, training, validation, and fine-tuning, all the way to deployment and documentation. You do not need any prior ML infrastructure in place.
At minimum, a clear description of what you need detected, details about your dataset (or what data you have available), your target deployment environment, and any specific accuracy or speed requirements. The more context you can share upfront, the faster we can begin. We will confirm exactly what is needed after reviewing your project details.
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Very good, and they are a pro.
Karthik Pillai's professionalism, responsiveness and cooperative spirit stands out in the realm of Data Science & ML. Working with him has been enjoyable and we look forward to continuing this fruitful partnership as we build our bespoke AI product.
Awesome as usual
Karthik Pillai is an exceptional data scientist who exceeded my expectations with his professional work and incredible attention to detail. Working with him was a breeze – he’s polite, punctual, and has a deep understanding of the project’s needs. Absolutely impressed!
They are a professional.
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