An honest check of whether you can build your first AI workflow in-house.
Use this to decide honestly whether you can build your first AI workflow in-house. Check what you already have. If most are checked, you can build it yourself. If several are blank, that gap is what a partner brings, and it is cheaper to borrow than to hire ahead of the work.
Do you have this today?
Senior AI-build talent close to the business. People who have shipped AI to production, not just experimented.
Access to frontier models (Claude, GPT, Gemini) and the judgment to pick the right one per task.
A safe way to feed your own data to a model, so it works from your documents and facts.
The ability to build a rules layer, fixed and explainable, for the decisions that must be auditable.
A place for a person to review and sign off, with the source on screen and every action logged.
Authentication and audit, named sign-ins tied to real people.
A validation harness, a test rig that runs the whole system against known-correct examples on every change.
A security boundary, your own cloud account under the right agreements, where sensitive data stays put.
Reading your result
Mostly checked. You likely have the capability to run a first workflow in-house. Start small, pick one workflow, and prove the return before you scale the team.
Several blank. Those gaps are exactly what an embedded partner supplies, senior people and a proven harness, so you can ship the first workflow now and build the in-house muscle alongside it.
Want a second read on this? Set up a conversation. We will map your highest-opportunity workflow with you, free.
Bob Klein, CEO · Digital Scientists [email protected] digitalscientists.com