Do I need clean data or a detailed brief?
No. Start with the decision or workflow you want to improve and the data you have, even if it is spread across spreadsheets or systems. We can scope a data or feasibility review before committing to a larger build. Please do not send confidential datasets through the enquiry form.
What happens after I send an enquiry?
I review your business problem and reply with questions or a suggested next step. If there is a fit, we arrange a scoping conversation and agree on deliverables, fees, and a timeline before work starts.
What is the AI & Data Opportunity Assessment?
It is a separately scoped, paid review of one business decision or workflow. You receive a problem and data review, practical options with value and effort assumptions, and a recommendation for a focused pilot with success measures. The introductory call establishes fit; the assessment scope, fee, and timing are agreed before work starts. If your requirements are already clear, we can discuss implementation directly.
How much does a project cost?
Pricing depends on data readiness, use cases, integrations, and support. Share a budget range if you have one. We can scope a focused first phase, and you receive a proposal before committing.
Will you recommend AI for every workflow?
No. We first look at the task, the data, and the cost of mistakes. A simpler automation or an ML model may be a better fit than an AI agent. Where AI is useful, we define evaluations, human review, and operational safeguards as part of the scope.
What kinds of AI agents can you build?
I can build agents that search internal knowledge, process documents, connect business systems, and coordinate multi-step workflows. The tools and models are chosen around your needs, existing systems, and constraints. We define permissions, approval points, evaluations, and failure handling around the task. A focused pilot helps establish what is reliable before expanding automation.
Can I hire you for data science or agent development separately?
Yes. You can engage me for data science and ML, agentic AI development, or a combination. For example, an ML model can generate a forecast and an agent can help your team investigate changes and prepare follow-up actions. The scope follows your business need.
How do you measure whether a model is useful?
We agree on the business decision and success measures first. Models are evaluated against a baseline, using historical backtesting for forecasting and appropriate tests for other use cases. Accuracy and commercial impact depend on your data and use case.
Can you work with my existing team and tools?
Yes. Engagements can cover a focused analysis, a workflow or model build, or support for your internal team. We agree on integrations, documentation, ownership, and handover in the project scope. I work remotely with teams worldwide.
