What we actually build
It is tempting, in a category as broad as AI, to position a firm as able to build anything. We have gone the other way. Most of what we do for executives in the first year of a relationship falls into three buckets, and saying so plainly has made it easier for everyone to scope work.
The first is workflow automation. These are the operations that your team executes the same way every week and that do not, on inspection, require human judgment at every step. Client intake. Onboarding paperwork. Invoice reconciliation. Report distribution. The work here is rarely glamorous. It is mapping what actually happens — as distinct from what the org chart says happens — and then replacing the manual steps with code that runs whether or not anyone is in the office. The payoff is not always speed. More often it is that the process becomes reliable, and your best people stop spending their best hours on it.
The second is custom AI assistants. An assistant, in the sense we use the word, is a narrow application of a language model that knows a specific body of knowledge — your products, your policies, your client history — and is connected to the tools it needs to do useful work with that knowledge. Assistants replace the first layer of repetitive questions your team handles every day, or give a client a better front door than a contact form. The critical design choice is scope. Assistants that try to do everything are brittle. Assistants that try to do one thing well are durable.
The third is reporting dashboards. This sounds mundane, and it is the engagement that most often surprises our clients with how much changes. The work is part data engineering, part editorial: identifying the handful of numbers that actually tell you how the business is doing, pulling them from the systems where they live, and presenting them in a format you can read in sixty seconds in the morning. The hardest conversation is almost always about which numbers matter. Once that is settled, the build is fast.
Under all three is the same pattern. Pick something specific. Deliver something working. Document it so someone else can own it. Repeat on the next thing. The firms that have told us they wish they had started earlier are uniformly the ones who resisted the urge to build a platform before they had built a tool.
— The IguanAI Team
If anything in this post reflects a problem you are thinking about, we would be glad to spend fifteen minutes on a call.
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