Projects
Keep every algorithm, source version, parameter set and experiment organized under one traceable identity.
↗GreenMoon AI gives trading algorithms a traceable identity — from source code and parameters to test runs, evidence and independent verification.
Trading research is often separated from the code and settings that produced it. GreenMoon keeps the complete lineage together, so a result can be traced back to an exact source version, parameter set and test environment.
From private research to published verification, every important artifact stays connected to the algorithm version that created it.
Keep every algorithm, source version, parameter set and experiment organized under one traceable identity.
↗Bind code, parameters, environment and test evidence into one reproducible verification record.
↗Discover published strategies through evidence, lineage and reproducible results — not marketing claims.
↗Understand code, compare versions, inspect changes and explain test evidence with an AI research layer.
↗A simple research chain designed to preserve context instead of losing it between source code, tests and reports.
Create or import a trading algorithm and establish its project identity.
Freeze the exact source and parameter state behind every experiment.
Record the environment, test window and execution conditions.
Attach reports, logs and artifacts to the version that produced them.
Publish a traceable evidence chain that others can inspect.
Verification is a chain, not a badge. Published evidence stays attached to the exact version that produced it, creating a durable record that can be inspected later.
project GM-0001 version v0.8.4 source_hash 8f3c…a921 parameters bound environment recorded test_run attached evidence attached lineage complete STATUS TRACEABLE
Public work should show what was tested, which version produced it and what evidence supports the result.
The next layer of GreenMoon will turn projects, versions, test runs and evidence into a working research environment. The public site explains the standard; the Lab is where the evidence chain is built.
Give every algorithm a persistent identity and history.
Bind source, settings and changes to immutable versions.
Capture test context, artifacts and verification state.
GreenMoon AI is building infrastructure for reproducible trading algorithm research.
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