Evidence-first data & AI
From raw signals,
to decisions you can trust
We build data and AI systems that make complex marketing and operating decisions reviewable, explainable, and easier to act on.
Evidence before automation
Human review built in
Deliberate data scope
HOW WE BUILD
Make the decision path visible
Start with the business question, connect only the evidence it needs, and make review points explicit.
Unify fragmented signals
Connect the systems, records, and events that currently leave teams with partial or conflicting views.
Model the decision
Turn raw activity into reviewable patterns, dependencies, and recommendations tied to the question at hand.
Keep people in control
Define where experts review, correct, approve, or escalate before an insight becomes an action.
DECISION PATTERNS
Where evidence-first systems can fit
Representative problem patterns, not claims of a prepackaged product or guaranteed outcome.
Marketing measurement and decisions
- Reconcile campaign, revenue, and customer signals around a defined decision
- Compare attribution output with incrementality evidence and known limitations
- Surface assumptions behind budget and audience recommendations
- Keep experts in the review path before recommendations become actions
Example decision pattern
Marketing
THE PROCESS
From evidence to action, with review in between
01
Scope and connect
Define the question and connect only the evidence needed to evaluate it.
02
Evaluate
Surface patterns, assumptions, uncertainty, and missing evidence.
03
Review and act
Let accountable people approve, correct, reject, or escalate the next step.
Frequently Asked Questions
Clear answers about our work, fit, and approach to data.
What does sig.ai build?
sig.ai builds data and AI systems for teams making complex operational and marketing decisions. The work spans data engineering, measurement and optimization, and TransferOS, a key-person diligence offering for buyers of owner-dependent businesses.
Is sig.ai only a marketing platform?
No. Marketing intelligence remains a core focus, including attribution, incrementality, and optimization. TransferOS applies the same evidence-first approach to a different problem: reconstructing how an owner-dependent business actually operates during an acquisition handoff.
How does a sig.ai engagement start?
We start with the decision you need to improve, the evidence available, and the constraints around access and review. That first conversation is used to define a narrow assessment or pilot rather than asking for a broad data handoff up front.
How does sig.ai approach sensitive data?
Data rights, purpose, access, retention, and deletion boundaries should be clear before sensitive content is requested. Early discovery can usually begin with non-sensitive business context and metadata, with deeper access scoped only when it is necessary and authorized.