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Services

Ask your data the hard questions. We build what answers them.

What's about to churn? Where's the fraud? What's the pattern no one has spotted yet? These answers are already in your data, they're just buried. We build the models and analysis that dig them out and put them in front of the people who decide, so your data does more than sit in storage.

2–4wks
to first working software
1–2wks
to project kickoff
100%
code & IP ownership
6–10yrs
average engineering experience

Predictive analytics & pattern discovery services

Every engagement starts with the question, not the technique. Pick a capability to see how we approach it.

We use your historical data to forecast what's coming, demand, churn, revenue, risk, so you can plan ahead instead of reacting. We're honest up front about how reliable a given prediction can be.

How we help

We build and rigorously validate forecasting models, and tell you the confidence behind them, so you act on predictions you can trust.

We build systems that spot the unusual as it happens, fraud, failures, outliers, so risk surfaces early, without burying your team in false alarms.

How we help

We tune anomaly-detection models to your real patterns and thresholds, so genuine risks stand out and noise stays quiet.

We dig through large datasets to surface the correlations, clusters, and segments that aren't visible by eye, the “we never realised these customers behave alike” insights that change strategy.

How we help

We apply clustering and pattern-mining techniques to reveal structure in your data, then translate it into something your team can act on.

We pull meaning from unstructured text, reviews, support tickets, survey responses, chats, so you understand what people actually feel and mean, at a scale no one could read manually.

How we help

We build NLP pipelines that extract sentiment, themes, and intent from text, turning thousands of messages into a clear signal.

We build models that recommend the next best action, product, price, or intervention, based on patterns in behaviour, so decisions get sharper and more personal.

How we help

We build recommendation and scoring models tuned to your goals, and put their output where it drives a decision.

An insight no one sees changes nothing. We put the output where the decision happens, into your product, your workflow, or a clear view your team already uses. For full dashboards and reporting platforms we work alongside our Business intelligence service; for the data foundation, our Data engineering service.

How we help

We deliver insight as an API, an alert, or an integration into your existing tools, so it reaches the decision-maker in the moment.

When data became an answer

View all case studies

The stack we build with

Standard, proven analysis and modelling tooling, chosen for the question rather than fashion. Pick an area to see what we reach for.

The everyday toolkit for exploring data and answering questions, expressive, well-supported, and familiar to every data engineer on the team.

Python
pandas
scikit-learn
R

Proven libraries for prediction and forecasting, chosen for the problem rather than the hype, from gradient boosting to time-series models.

XGBoost
Prophet
TensorFlow
PyTorch

For pulling sentiment, themes, and intent out of unstructured text at a scale no one could read by hand.

spaCy
NLTK
Hugging Face transformers

Detection models tuned to your normal patterns, run in batch or on live streams, so genuine anomalies surface early without noise.

Streaming analytics
Custom detection models

Getting the insight to where the decision happens, as an API, an alert, or an integration into tools your team already uses.

REST APIs
Webhooks
MLOps tooling

Models packaged and deployed to run reliably and scale with demand, on infrastructure that stays observable and cost-aware.

AWS
Docker

Our predictive analytics process

Seven steps, run in order, from framing the question and checking the data can answer it through to delivering the insight where decisions happen and refining it over time.

01

Define the question

We start with the specific decision you're trying to make, not the algorithm, because a sharp question is what makes an answer useful.

02

Assess the data

We check honestly whether your data can actually support the answer you want, and tell you before you invest if it can't.

03

Prepare & explore

We clean, shape, and explore the data to understand what's really in it, surfacing quality issues and early signals as we go.

04

Build & validate the model

We build the forecasting, detection, or pattern model and validate it properly against held-out data, not just the numbers that flatter it.

05

Measure confidence honestly

We quantify how reliable the result is and say so plainly, so you know exactly how much weight a prediction can bear.

06

Deliver where decisions happen

We put the insight into an API, an alert, or the tools your team already uses, so it reaches the decision-maker in the moment.

07

Monitor & refine

Patterns drift over time, so we monitor accuracy in production and refine the model as your data and the world change.

Predictive analytics experts, AI-augmented

These are the AI coding tools our engineers use to ship faster and keep code clean, distinct from the AI systems we design and build for you.

Claude CodeGitHub CopilotCodexCursorReplitGeminiOllamaWindsurf

We use these tools inside strict guardrails, every line is reviewed by a person. See how we build →

1

Senior Predictive analytics engineers

Engineers with real, hands-on predictive analytics experience who take ownership of the work, not juniors learning on your budget.

2

Production-grade delivery

We take work from prototype to production, with testing, monitoring, and clean handover, not demos that stall after the pitch.

3

Security & compliance

Safeguards from day one. We build to and align with the standards regulated industries expect, including HIPAA, SOC 2, and ISO 27001.

We've turned data into answers across fintech, talent, and more.

See how we approach your industry
Engagement

How you'd work with us on Predictive analytics

Pick the level of ownership that suits you. We shape the engagement around your goals.

1

Staff augmentation

Add senior Predictive analytics engineers to a team you already have.

2

Dedicated team

A committed Predictive analytics team that runs like your own.

3

Full delivery

Hand over the build and we deliver it end to end.

Explore engagement models

Predictive analytics FAQ

Got a question your data should be able to answer?

Tell us the question, and we'll tell you honestly whether your data can answer it, and how we'd build what does.

Book a discovery call