Data and feasibility review
An assessment of available data, quality constraints and the suitability of the proposed use case.
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Find where data and AI can make a practical difference. We begin with the decision or workflow you want to improve, then assess whether analytics, automation or machine learning is an appropriate fit.
Discuss your projectAn assessment of available data, quality constraints and the suitability of the proposed use case.
An analytical workflow or prototype evaluated against agreed business and technical criteria.
A path toward product integration, including evaluation, monitoring and human review requirements where needed.
Final scope and deliverables are agreed after discovery and before work begins.
Identify the business problem, a baseline and measurable evaluation criteria.
Review data availability, quality, access and handling requirements.
Test a focused approach and examine errors, limitations and operational costs.
Use the evidence to decide whether to integrate, iterate or stop the experiment.
The requirements depend on the use case. We first assess your data and whether existing models, simpler analytics or workflow automation could meet the need.
No fixed accuracy is promised before evaluation. We agree suitable metrics, test against representative examples and document limitations before deciding on deployment.
Share your goals, current situation and constraints so we can identify a useful next step.
Discuss your project