How it works
An answer you can audit — not a black box.
We don’t ask you to trust a brand. The system shows you the method, the sources, and the confidence behind every claim — and an expert owns the parts where being wrong is expensive. Here’s exactly how it runs.
The pipeline
Query → Gather → Synthesize → Sign-off → Deliver
The system runs the whole pipeline — wide and fast. A person concentrates at the one point where being wrong is expensive: signing off on the risk. And every project ends by adding to what we already know.
01 · Query
You define the decision — the market and the move. No long onboarding.
02 · Gather
The system starts from what we’ve already verified, then pulls live ground data: trade, regulatory, competitor, channel.
03 · Synthesize
It resolves all of that into one recommendation, with a draft confidence score on every claim.
04 · Sign-offsign-off
An expert owns and signs the risk — every checkable claim traced to a real, tiered source.
05 · Deliver
A clear, sourced answer ships — and what we verified is saved, so the next project starts ahead.
Why it gets better
Every project makes the next one sharper.
This isn’t consulting that starts from zero each time. We keep what we learn, so the system gets better with use — and harder to catch the more markets we cover.
We keep what we learn
Every project adds verified intelligence to a private library that’s ours alone — not thrown away when the answer ships.
It costs less to run
The next project starts from what we already know, instead of rebuilding it from scratch.
It gets more confident
The more markets we cover, the more each new answer can lean on what we’ve already checked.
The source-tiering rule
Every checkable fact is tagged by its source.
Primary / official
KOTRA, KITA, UN Comtrade, government registries, regulators. The bedrock.
Reputable secondary
Established industry and research sources.
AI-inferred
Always flagged as inference, never sold as fact.
The rule: anything specific and checkable — a number, a regulation, a name — is traced to a tiered source and confirmed by an expert before it ships, then saved so we can stand behind it later.
Confidence, stated
We’d rather tell you a number is 0.74 than pretend it’s certain.
Every claim carries a confidence score, and every answer carries an overall confidence band. Calibrated honesty is what lets you weight the decision correctly — and defend it afterward. It’s also what keeps the library we build trustworthy as it grows.
Example
Where a person signs off
Software does the breadth. A person owns the risk.
Software handles the research, synthesis, translation, and monitoring. A person is accountable only where accuracy matters most — and that’s why we don’t blow up.
Data trust
Your data is never used to train third-party models.
Sensitive material is handled under a stated policy. We build to PIPA and the AI Basic Act’s expectations. A domain expert is accountable for what we ship. With this buyer — and Korea’s regulators — saying that plainly is part of the product.
Start here
See the system run on a real query.
Click any claim in our sample to watch the evidence — source, method, and confidence — slide out.