- Opportunity identification
- Data readiness
- Technical feasibility
- Build vs buy analysis
- Risk & limitations
- Business case & ROI
- Opportunity identification
We look at your business operations, products, and customer interactions to identify where AI could have a meaningful impact. Not every process benefits from AI, and not every AI application is worth the investment.
We focus on use cases where the value is clear and measurable – things like reducing manual processing time, improving decision quality with better data, or adding capabilities to a product that would be impossible to build with traditional software. If a simpler solution would solve the problem just as well, we'll say so.
- Data readiness
AI systems are only as good as the data behind them. We assess what data you currently have, how clean and structured it is, whether there's enough of it, and what gaps would need filling before any AI solution could work reliably.
This is where a lot of AI ambitions quietly die. If the data isn't there or isn't usable, it's better to know upfront than to discover it mid-build. Sometimes the right first step isn't building an AI feature – it's getting your data in order so you can build one later.
- Technical feasibility
Not everything that sounds possible with AI is practical to build at a reasonable cost. We evaluate whether the use cases we've identified are technically achievable given your data, your infrastructure, and the current state of the technology.
This includes assessing which approach fits best – whether that's integrating a frontier model like GPT or Claude through an API, building a RAG system over your own data, or something else entirely. We match the approach to the problem, not the other way around.
- Build vs buy analysis
For many AI use cases, there's already a product on the market that does most of what you need. For others, a custom build is the only way to get the result you're after.
We help you make that call honestly. Building custom AI is expensive, and if an existing tool gets you 80% of the way there, that might be the smarter move. If off-the-shelf options don't fit your requirements, data, or security constraints, we'll scope what a custom solution would involve.
- Risk & limitations
AI systems have failure modes that traditional software doesn't. Models hallucinate. Outputs vary. Performance degrades when data drifts. Bias in training data leads to biased results.
We identify these risks for your specific use case and design around them. That might mean adding human review steps, setting confidence thresholds, or defining clear boundaries around what the AI is and isn't responsible for. Knowing the limitations upfront is what separates a useful AI feature from an embarrassing one.
- Business case & ROI
We pull everything together into a clear business case: what the opportunity is, what it would cost to implement, what the expected return looks like, and what the risks are. Something concrete enough to make a decision with.
If the numbers don't stack up, we'll tell you. There's no point building an AI feature that costs more to develop and maintain than the value it creates. And if the case is strong, you'll have the evidence to get it funded and the plan to get it built.
