Applied AI for decisions that matter
sig.ai builds evidence-first systems that turn fragmented marketing and operating signals into decisions people can review, trust, and act on.
OUR APPROACH
Build the review path, not just the model
Trust comes from knowing what evidence was used, where judgment entered, and who can correct the result.
Start with evidence
Connect recommendations to the records, events, and assumptions that produced them.
Design the review path
Make it explicit where people correct, approve, reject, or escalate a proposed action.
Scope data deliberately
Define purpose, authority, access, retention, and deletion before deeper data access.
WHERE WE FOCUS
One operating principle, three practical entry points
DATA & AI SYSTEMS
Decision infrastructure
Connect fragmented business signals and turn them into reviewable models, workflows, and recommendations.
Explore the platform →MARKETING INTELLIGENCE
Measurement and optimization
Support attribution, incrementality, budget allocation, and other decisions where evidence matters more than dashboards alone.
See marketing solutions →TRANSFEROS
Key-person diligence
Help buyers test whether seller operating judgment can be reconstructed from real cases, records, and targeted correction.
Learn about TransferOS →FOUNDER
Yong Huang
Founder & CEO
Yong founded sig.ai to apply data engineering and AI to business decisions that are difficult to automate safely. The company is based in Mercer Island, Washington.
View LinkedIn profile
Company facts
Founded in 2019
Based in Mercer Island, Washington
Focused on evidence-first data and AI systems
Marketing intelligence and TransferOS are current entry points
COMMON QUESTIONS
About sig.ai
What does sig.ai do?
sig.ai builds data and AI systems for complex business decisions. Current focus areas include marketing measurement and optimization, data and decision infrastructure, and TransferOS key-person diligence for owner-dependent business acquisitions.
Is sig.ai only for marketing teams?
No. Marketing intelligence is one focus area, but the broader approach applies wherever important decisions depend on fragmented data, tacit knowledge, or a review process that cannot safely be removed.
How does sig.ai approach sensitive data?
We begin by clarifying the business purpose and data-rights path. Early discovery should use non-sensitive context and metadata where possible; deeper content is scoped only when it is necessary, authorized, and governed by clear access and retention boundaries.
How can we evaluate whether there is a fit?
Send the decision or workflow you are trying to improve, the evidence currently available, and the constraint that makes the problem hard. We will use that context to determine whether a focused assessment or pilot is practical.
Bring us the decision that still feels too manual
Share the workflow, the evidence you have, and the constraint that keeps the team from moving faster.
Discuss a project