Description
What this service covers
Many machine learning projects stall as soon as someone asks whether the data can actually back the idea, so we answer that question up front. We start from your proposed use case, examine the data you really have and train a baseline model to measure how much useful signal exists. The result may be a tuned model, or it may be that a simple rules engine delivers almost the same value at a fraction of the cost.
What you receive
- Review of data volume, quality, labels and class balance
- Baseline model trained and evaluated on your data
- Direct comparison against a simple rules-based alternative
- Analysis of which features carry the predictive signal
- Cost and effort estimates for moving to production
- Written recommendation, which could be to stop here
- Reproducible notebook and code that you keep
The work in 4 stages
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01
Stage 1: Problem definition
We pin down what is being predicted, which decision it informs and what success means.
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02
Stage 2: Data profiling
We check the data for gaps, leakage and label quality.
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Stage 3: Baseline testing
We train a first model and compare it with the rules-based option.
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Stage 4: Findings call
Results, figures and a build estimate are presented to you on a call.
Who it suits, and what we need from you
Ideal for
- Teams under pressure to use AI with no clear use case
- Organisations with a specific prediction problem and unproven data
- Boards that want a business case before hiring a data scientist
What we need from you
- A data extract, with sensitive fields masked where necessary
- A clear statement of the decision the model should improve
- Access to the person who knows how the data is collected
You share these through the brief on your order page after checkout.
What changes for your team
- A go or no-go decision backed by a measured baseline
- Data quality issues found before they can derail a build
- Sometimes a simpler solution that needs no model
Questions about this service
What if the study says no?
How much data is enough?
Will you sign a confidentiality agreement?
This is a remote service: nothing is shipped physically, and the work is delivered into systems you control. See delivery and handover and refunds and cancellation for the full terms.
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