practice 03

Technology strategy.

Which AI and technology bets are worth making, and which ones to leave alone. One of our founders builds computer vision models and has taken several into production, so we know the gap between a demo and a system that works.

You get A shortlist of AI and technology bets, with the cost, the payback and a roadmap.

Talk to us about technology strategy

typical questions

Questions we help answer.

Which of our AI ideas will pay for themselves, and which are a distraction?
Should we build this ourselves, buy a product or work with a partner?
What would it take to move this from a pilot to everyday use?
Before we invest in this company, does its technology hold up?

services

What the work covers.

Most projects combine two or three of these. Each one starts from the decision in front of you.

01
AI opportunity assessment
Every AI idea on the table, costed, with a realistic payback and the data it would need.
02
Digital transformation
Which processes to change first, in what order, and what the business gets back from each step.
03
Technology roadmaps
What to build or buy over the next 12 to 24 months, in an order that follows the business plan.
04
AI and analytics use cases
Specific, costed use cases drawn from how your operations and data work today.
05
Build vs buy
Cost, time to market and risk for building, buying or partnering, side by side.
06
Technical due diligence
An independent read of a company's product, architecture and technical risks before you invest or acquire.
07
Product and technology strategy
What the product should do next, and what the technology underneath needs to support it.