AI Consulting
Clarity on what to build, what to skip, and what order to do it in — before a line of code is written.
Most AI consulting engagements start with the same problem: a business knows it wants to use AI but isn't sure where to start or whether what it's considering is actually feasible with its existing data and infrastructure. We work through that question directly — not with a slide deck of general AI trends, but with a structured review of your actual software, data, and workflows.
A typical consulting engagement covers: which use cases in your business are technically feasible with current AI APIs, which require data you don't yet have, what the realistic cost and latency look like for each option, and what a sensible implementation order is given your team's bandwidth.
The output is a prioritised list with enough specificity to brief a developer — not a roadmap of aspirations. If the answer is "the thing you want to build isn't the highest-value thing you could build," we say so.
What a consulting engagement covers
Feasibility Review
Which use cases work with your current data and infrastructure — and which don't yet.
Use Case Prioritisation
A ranked list based on business impact, technical complexity, and data readiness.
Cost & Latency Modelling
Realistic estimates for AI API usage at your actual volumes.
Implementation Roadmap
Specific enough to brief a developer — not a list of aspirations.