AI-assisted. Paper-first.

Test the signal.
Show the truth.

Build an AI-assisted market experiment, track simulated trades, and share what actually happens. SignalNest starts with evidence—not promises of profit.

The $20 launch blueprint · Start with simulated trades · No guaranteed returns

SignalNest hero
01 / THE EXPERIMENTObserve. Record. Improve.

Our founding commitments

Simulation before real capital

Wins, losses, fees, and drawdowns

Feedback before paid features

The action map / 7 days

A small start.
A measurable experiment.

For curious builders, beginner Python users, and market learners. Pick one market. Make every decision explainable.

01 / DAYS 1–3

Build the signal.
Keep the receipts.

Start with a single pair, such as BTC/USDT. Use public data, simple indicators, and AI-assisted explanations to form a testable hypothesis.

EXPERIMENT SPECPAPER ONLY
Market
BTC / USDT
Inputs
Price + indicators
Record
Entry / exit / fees
Evaluate
Losses + drawdown

Illustrative workflow, not a live signal or performance result.

02 / DAYS 4–5

Turn the log into the story.

Publish short screen recordings: what the bot expected, what happened, and what you learned. Show losing trades alongside winning ones.

03 / DAYS 6–7

Build with your audience.

Open a free signal community, collect feedback, and ask which analytics people would actually pay for. Validate demand before adding complexity.

Create your starting point

Access / pricing

Validate first. Upgrade later.

Explore available plans below. Paid access buys tools and learning—not a promise of trading returns.

Free

For individuals getting started

$0/month

  • 1 workspace
  • Up to 3 team members
  • Basic analytics
  • Community support
Get Started

The $20 blueprint is a startup budget, not an investment requirement. Free tools can cover analysis, automation, and content; keep essential living expenses separate.

Your next move

Less hype.
More hypotheses.

Your first milestone isn’t a profit screenshot. It’s a clear setup, an honest log, and something worth learning from.

Start your experiment

Before you begin

Historical and simulated performance are not reliable indicators of future results. Never risk money you cannot afford to lose.