01
Import the evidence
Bring in qualifying historical trades through a supported file or account connection, then keep sample data separate from real analysis.
Owned product case · financial technology
Trade data in.A decision rule out.
TradeInsights shows how Tier9AI turns a broad AI product into a controlled operating loop: historical records become inspectable findings, explicit user decisions, and monitored follow-through.
Relationship
Tier9AI-owned product
Role
Owner-operator and product lead
Status
Live subscription software
Domain
Trading analytics
The product problem
A dashboard can report the past and still leave the next decision untouched.
Trading data is commonly split across broker exports, notes, screenshots, and memory. Conventional dashboards can calculate totals, while generic AI can produce a confident explanation without showing whether the sample supports it.
The operating challenge was to connect those pieces into one accountable job: help a trader identify a supported historical pattern, decide whether it deserves an execution rule, and review what happened in a later sample.
Product thesis: analysis is useful only when the evidence is inspectable and the next action remains under the user's control.
The production workflow
Four stages. One evidence trail.
The product separates calculation, AI assistance, and human judgment so each layer has a clear job and a visible boundary.
02
Calculate before explaining
Deterministic performance, risk, timing, and behavior measures establish the facts before optional AI-assisted review begins.
03
Inspect the finding
A useful finding exposes its method, supporting records, confidence, and limitations instead of asking the user to trust fluent output.
04
Create a rule and monitor
The user decides what action is justified, records an execution rule, and compares the next sample rather than treating analysis as a signal.
Founder-led decisions
Product, controls, and commercial path point at the same outcome.
This is the work Tier9AI is built to own: narrow the job, define the decision rights, make first value measurable, and align the product promise with the production workflow.
One first-value threshold
Twenty qualifying imported trades unlock the First Value Report. The activation event is evidence reviewed—not an account created.
One clear value loop
Import, finding, rule, and monitoring form a single operating journey instead of a disconnected collection of AI features.
One explicit boundary
The product analyzes historical records. It does not place trades, predict markets, or promise improved returns.
One accountable decision-maker
AI can help organize and explain the evidence. The trader decides whether a finding deserves a rule and owns the action that follows.
What is live
Success shown as shipped capability—not fictional ROI.
The public evidence is a coherent, commercially available product and its operating controls. No claim is made here about customer trading performance, revenue, or adoption volume.
Inspect TradeInsights.ioProduction evidenceStatus
A public product with diagnostic, Premium, and Pro access pathsLive
A defined first-value gate based on qualifying imported recordsLive
Historical analytics shown separately from optional AI-assisted reviewLive
Findings designed around method, confidence, evidence, and limitationsLive
Historical-analysis boundaries with no signals or trade executionLive
Focused workflows for behavior, prop risk, and multi-account reviewLive
Commercial path
Free diagnostic → ongoing Premium or Pro system
The accountable scorecard
Measure the operating loop before claiming the business result.
These are the measures designed into the product. They are not presented as published customer outcomes; they define what should be instrumented and reviewed as the evidence base grows.
01
Activation
Qualifying trades imported and First Value Report viewed
Did the user reach evidence-backed value?
02
Adoption
Finding inspected and converted into an explicit rule
Did analysis change a controllable decision?
03
Continuation
A later sample reviewed against the recorded rule
Did the product close the feedback loop?
04
Trust
Method, evidence, confidence, and limits remain reviewable
Can the claim survive scrutiny?
Apply the operating pattern