v0.1.0 — open source
Simulate how any company
reacts to change
Build digital twins from SEC filings. Test scenarios. Understand corporate behavior before it happens.

ecosystem
Six packages. One platform.
Each repo stands alone. Together, they model how companies behave under pressure.

mimic
AvailableCore framework. Build company twins from SEC filings.

mimic/world
Coming SoonMulti-company simulation. Cascade effects across the economy.

mimic/bench
AvailableValidation benchmark. 200 events, 2,800+ labeled pairs.

mimic/signal
BetaReal-time event detection from news and filings.

mimic/sim
AvailableEconomic formulas. DCF, CAPM, supply chain models.

mimic/forecast
Coming SoonTime series prediction with TimesFM, Chronos, or custom.
interactive demo
Try it yourself
Type commands to explore the API. Try help, twin WMT, or simulate.
Python SDK
from mimic import Twin
twin = Twin.from_ticker("AAPL")
result = twin.simulate(
event="Taiwan conflict",
severity=0.8
)
print(result.financial_impact)Economic Formulas
from mimic.formulas import dcf_impact
# Calculate EV change from
# 20% FCF reduction
delta = dcf_impact(
base_fcf=50_000,
shock_pct=-0.20,
wacc=0.09
)benchmark
Validated against reality
Every simulation is tested against 200 historical events. We compare predictions to what actually happened.
200
Historical Events
50
Companies Tested
2,847
Labeled Pairs
71.3%
Avg Fidelity
$ mimic benchmark --events=crisis_2015_2024
Running benchmark on 50 S&P 500 companies...
Event: COVID-19 pandemic onset (2020-03)
WMT predicted: "Accelerate e-commerce, stockpile essentials"
WMT actual: Matched (e-commerce +74% YoY)
Score: 0.84
Overall Results:
Accuracy: 71.3% across 2,847 test pairs
economic formulas
dcf_impact()EV change from cash flow shockcogs_sensitivity()Input cost → margin impactaltman_z()Bankruptcy risk scoresupplier_hhi()Supply concentration (HHI)capm_response()Stock reaction to marketcascade_propagate()Supply chain propagation