AI and ML development
Custom machine learning models that forecast outcomes, read documents and check images, for teams with a clear question their data can answer.
- You get
A tested model, connected to your systems
- After the call
A written proposal, usually within a week
What problems does machine learning solve?
It turns the patterns in your historical data into forecasts, labels and checks you can act on.
Forecasts built on guesswork
Demand, risk or workload is planned from rules of thumb and spreadsheets.
Documents read by hand
Forms, invoices and reports are read and re-keyed by people.
Checks done by eye
Quality control and inspection depend on someone looking at every item.
What does AI and ML development include?
A model built for one clear question, tested against a baseline you agree, and connected to the way you work.
A data check first
We audit data quality and test assumptions before any model is trained.
A tested model
Forecasting, classification, computer vision or document extraction, its accuracy measured against the baseline.
Results you can explain
Hypothesis testing to separate cause from correlation, with the confidence stated.
Integration and monitoring
The model runs in your systems or reports, with its accuracy tracked as the data changes.
How does a machine learning project run?
We check the data first, then build the model.
Check the data
We audit quality, find patterns and confirm your data can answer the question.
Build and test
Feature engineering, training and testing against the agreed baseline, with what-if scenarios.
Put it to work
We connect the model to your systems or reporting and set up monitoring.
Monitor and retrain
We watch its accuracy and retrain it when the data changes.
What have we built for clients?
From one client project that included AI and ML development.
Professional services
RN Insight Studio
An AI research assistant that turns the latest news into thought leadership
Nothing is posted automatically: a person reviews every draft.
Read the case study
Who will you work with?
Founders with 40+ years’ combined experience, delivering for Barclays and JPMorgan Chase. They lead every project.
Mahesh Pappu
Co-founder and CEO
Senior data science and risk modelling roles at Barclays and Discover Financial Services.
Pavan Gathala
Co-founder and CTO
Managed critical infrastructure at TCS for clients including JPMorgan Chase.
Every project is run from the UK.
More about the foundersHow do we start?
With a call, then a written proposal.
A free 30-minute call
We talk through what you want to achieve, the systems involved and your timeline.
A written proposal
We send a written proposal with the scope, timeline and cost, usually within a week.
Frequently asked questions
What is the difference between machine learning and agentic AI?
A machine learning model makes a prediction or a classification, such as a forecast or a label on a document. An agent carries out a task. A project can use both: a model makes the prediction and an agent acts on it.
How much data do we need?
It depends on the question. The data check at the start tells you whether your data can support a model, before any model is trained.
Can you explain how a model reaches its results?
Yes. We test assumptions, report accuracy against the baseline and state the confidence behind each result, so a decision can be explained to a reviewer or a regulator.
Who owns the code and models?
You own the code and models we build for you once the project is paid for.
How long does it take?
It depends on the scope. The written proposal after the call sets out the timeline for your project.
How much does it cost?
Every project is scoped individually, so there is no price list. After the free 30-minute call we send a written proposal with the scope, timeline and cost, usually within a week.
Often combined with
Tell us what you want to build
A free 30-minute call is the quickest way to find out whether we can help.