Data engineering and MLOps
Automated pipelines, dashboards and data platforms that give your team and your AI clean, current data, for organisations whose data is scattered or handled by hand.
- You get
Automated pipelines, quality checks and dashboards
- After the call
A written proposal, usually within a week
What problems does data engineering solve?
It replaces manual exports and scattered spreadsheets with data that arrives clean, checked and on time.
Scattered sources
Data is spread across tools and systems, with no single view.
Manual work
Teams spend hours each week exporting, consolidating and reconciling data.
Out-of-date figures
Decisions are made on information that is already days or weeks old.
What does data engineering and MLOps include?
Foundations first, then scale: automate the data work you do today, and build a platform when AI and analytics need one.
Automated pipelines
Your business tools connected, with no manual exports or spreadsheet updates.
Dashboards
One source of truth for your team, updated automatically.
Quality checks
Automated validation that catches errors before they spread.
A data platform and MLOps
A cloud platform with model deployment and monitoring, encryption and audit trails.
How does a data project run?
We fix the foundations first, so your data is clean and current before anything is built on top of it.
Map your data
We find where your data lives, how it moves and where it breaks.
Automate the foundations
Pipelines, quality checks and dashboards for the data work done by hand today.
Build the platform
When AI and analytics need it: a cloud data platform with model serving and access controls.
Run and support
Monitoring, fixes and model updates, so the data keeps arriving.
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.
- Certification
Cyber Essentials certified
- Endorsement
Innovator Founder
Supported by the Department for Business and Trade’s Global Entrepreneur Programme.
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
Do we need a data platform before we can use AI?
Not always. You can start by automating the data work done by hand today, and build a platform when AI and analytics need one.
What is MLOps?
The practice of deploying, monitoring and updating machine learning models in production, so they keep working as the data changes.
Where is our data hosted?
Where data is hosted and processed is agreed with each client before any build starts, including UK or EU hosting.
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.