01 / UNDERSTAND THE WORK
Observe
Sit with the people doing the job. Map the real process, including workarounds and exceptions.
Process map
- EMAILOrder received
- AIExtract details
- RULESCheck inventory
- DECISIONRoute the order
- HUMANReview exception
- ERPCreate order
Independent AI consulting / Hypothesis One
AI, built for
the real world.
AI agents and automations that survive
contact with your operation.
For businesses that make things,
move things, and service the physical world.
The demo ends.
The operation keeps going.
Your operation has exceptions.
Your AI should be built for them.
I build around the real process: the missing data, the workarounds, and the decisions that need a person. The goal is a system people can rely on after launch.
Four ways
to start.
Fixed scope. Clear deliverables. A defined handover.
Find the right process to automate.
I map how the work actually gets done and assess which opportunities are worth pursuing.
- A process map, including exceptions
- A ranked roadmap based on value, feasibility, and risk
- Build specifications your team can use
A GOOD FIT WHEN
You need to decide where to start.
THE METHOD
Form the hypothesis.
Then try to disprove it.
02 / DEFINE THE TEST
Hypothesize
Agree on what should improve, how to measure it, and the baseline to compare against.
A measurable claim
03 / PUT IT TO WORK
Build
Build the smallest complete system. Test it with real users and data, with error handling and human checkpoints.
A system in production
04 / CHECK THE RESULT
Measure & hand over
Compare the outcome to the baseline. Hand over the code, access, documentation, and a walkthrough.
Measured results and ownership
Tools change.
Judgment carries over.
Open and closed models
- Frontier models
- Claude, GPT, and Gemini for everyday work and custom workflows
- Open models
- Open-source and open-weight alternatives, run locally or hosted
- Choosing the fit
- Balance capability, control, and cost against the task
DAIRIS ZARINS / FOUNDER
I ran the operation
before I automated it.
I spent a decade running e-commerce fulfillment operations.
I know what happens when a machine goes down, a carrier changes a cutoff, or the data does not match reality. Those exceptions are where an automation earns its place.
I also worked hands on inside an internal ERP build, translating operational problems into requirements and working through the edge cases with engineers.
Today, I lead AI transformation inside a large organization, developing practical skills, evaluating tools, and helping teams put agents to work.
No vendor commissions.You work directly with me.Your systems stay yours.
Before
getting started.
Usually not. Handling messy inputs can be part of the system. If missing or unreliable data would block the work, I identify that before the build.
START A CONVERSATION
What is
slowing
you down?
Tell me about the process, what you have tried, and what better would look like. I usually reply within two business days.
dairis@hypothesisone.xyz