Decisions made on gut feel
Forecasts and risk calls rely on spreadsheets and intuition.
Machine Learning & Computer Vision
Machine learning and computer vision development
Not every problem needs an LLM. We build classical machine learning, deep learning and computer vision models for prediction, forecasting, classification and detection, with rigorous validation and deployment so the model keeps performing after launch.
What you can expect
- 95%+ backtested accuracy on a real-time prediction model
- Medical image classification with transfer learning
- Models deployed with monitoring, not left in notebooks
(01) The problem
Why teams come to us for Machine Learning & Computer Vision.
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Images reviewed by hand
Inspection and screening are slow and inconsistent.
Models that never leave the notebook
Promising experiments stall without data pipelines and deployment.
Accuracy that decays
Models drift as data changes, and nobody notices until results suffer.
(02) Use cases
What we build with Machine Learning & Computer Vision.
- 01
Medical imaging
CNN classifiers for brain-tumor detection and diabetic-retinopathy screening.
- 02
Forecasting and demand planning
Time-series models for demand, revenue and capacity.
- 03
Sports and outcome prediction
Real-time probabilistic models; our NHL predictor reached 95%+ backtested accuracy.
- 04
NLP classification and extraction
Classify text, detect intent and extract entities at scale.
- 05
Visual inspection
Detect defects, objects and anomalies in images and video.
- 06
Analytics programs
Statistical modelling and data science for ongoing decision support.
Deliverables
Everything you need to run it in production.
- Data audit and feature engineering
- Model development and experiment tracking
- Validation, backtesting and bias checks
- Deployment as APIs or batch jobs
- Monitoring for drift and performance
- Documentation and a retraining plan
Our approach
How we deliver reliable results.
- 1
Frame the decision
We define what the model must predict, how it will be used and what accuracy is worth.
- 2
Validate honestly
Hold-out sets, cross-validation and backtesting on historical data, with metrics agreed up front.
- 3
Deploy and monitor
Models ship as services with drift monitoring and a retraining path.
Proof
Related case studies, with real numbers.
Healthcare
Medical Imaging AI
Deep-learning models for brain-tumor detection and diabetic-retinopathy screening
- screening models
- 2
- screening models
- deep-learning architecture
- CNN
- deep-learning architecture
- learning from pretrained vision
- Transfer
- learning from pretrained vision
Sports analytics
Real-Time Sports Outcome Predictor
A probabilistic NHL match predictor with 95%+ backtested accuracy
- backtested accuracy
- 95%+
- backtested accuracy
- predictions
- Real-time
- predictions
- statistical model
- Poisson
- statistical model
Finance & investment
Multi-Agent Financial Document Intelligence
Specialized AI agents that turn earnings calls and financial PDFs into client-ready reports
- specialized CrewAI roles
- Multi-agent
- specialized CrewAI roles
- transcript to report
- End to end
- transcript to report
- structured output
- Client-ready
- structured output
Also delivered
- Ongoing data science program for analytical projects since 2024
- Code contributions to Deep Ivy's machine-learning frameworks
Technology
Tools we use for Machine Learning & Computer Vision.
Model-agnostic and cloud-agnostic: we pick the right components for your data, budget and compliance requirements.
- Python
- PyTorch
- TensorFlow
- Keras
- scikit-learn
- XGBoost
- Hugging Face Transformers
- OpenCV
- YOLO
- Pandas
- NumPy
- MLflow
Industries we serve
Engagement models
Flexible ways to work, one standard of delivery.
Start small with a discovery sprint or an audit, or go straight to a production build. Most projects start from $5,000, scoped after a free strategy call.
1–2 weeks · fixed scope
AI Strategy & Discovery Sprint
Teams validating an AI opportunity before committing a budget.
- Use-case and ROI workshop
- Data and systems audit
- Architecture blueprint
- Risk and compliance review
- Build plan with estimates
4–12 weeks · milestone-based
Production Build
A defined RAG platform, AI agent, automation or AI product, delivered end to end.
- Architecture and full build
- Evaluation suite and QA
- Security and compliance controls
- Deployment and monitoring
- Documentation and handover
Monthly retainer
Dedicated AI Engineering
Product and platform teams with an ongoing AI roadmap and no time to hire.
- Senior AI engineering capacity
- Weekly planning and demos
- Continuous evaluation and monitoring
- Model and cost optimization
- Scale up with vetted specialists
1–3 weeks · fixed scope
AI Audit & Evaluation
An existing LLM, RAG or agent system that underperforms or is changing hands.
- Architecture and code review
- Answer-quality evaluation
- Security, PII and compliance review
- Cost and latency analysis
- Prioritized remediation report
Not sure which model fits? A free 30-minute call is enough to decide.
Book a free strategy callMachine Learning & Computer Vision FAQ
Common questions about Machine Learning & Computer Vision.
Can't find your answer? Ask us on a free strategy call or send a short brief.
Do we need machine learning or an LLM?
If you are predicting a number, a category or a probability from structured data or images, classical machine learning or deep learning is usually cheaper and more accurate. LLMs shine with language. We will recommend honestly.
How much data do we need?
It depends on the problem. Transfer learning lets image models perform well with hundreds to thousands of labelled examples; we assess your data before committing.
How do you validate accuracy?
Hold-out sets, cross-validation and backtesting on historical data, with the success metric agreed before we train.
Can you deploy the model into our systems?
Yes: as an API, a batch pipeline or embedded in your application, with monitoring for drift.
Do you work with medical data?
Yes, with de-identification and access controls appropriate to healthcare data. We have built medical imaging classifiers.
Taking on new projects
Let’sbuild.
Have an AI project in mind? Let’s make it real.
Book a free 30-minute strategy call with our founder. You’ll leave with a clear view of the right architecture, timeline and next step, whether or not we work together.
- Reply within 24 hours
- NDA before you share anything confidential
- You own the code, prompts and documentation
- Hours overlap with US, UK, EU and Gulf teams