EVLV vs FTNT

Evolv Technologies Holdings, In vs Fortinet, Inc. — Valuation Comparison 2026

EVLV

Computer Peripheral Equipment, NEC
Evolv Technologies Holdings, In
Quality
7.1
out of 10
Value Trap
36
LOW
Price
$6.45
Last close
Models
12/13
Active
VS

FTNT

Computer Peripheral Equipment, NEC
Fortinet, Inc.
Quality
10.0
out of 10
Value Trap
18
SAFE
Price
$137.97
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType EVLV Fair ValueEVLV Upside FTNT Fair ValueFTNT Upside
Bayesian DCF Intrinsic $1.70 -73.7% $59.67 -56.8%
Earnings Power Value Intrinsic $0.73 -89.9% $26.74 -80.6%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for EVLV vs FTNT — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

EVLV vs FTNT — Which Stock Is More Undervalued?

FTNT scores higher with a 10.0/10 quality rating vs EVLV's 7.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Evolv Technologies Holdings, In (EVLV) and Fortinet, Inc. (FTNT) across 13 institutional-grade valuation models reveals how each company's intrinsic value stacks up against its market price. CirclFi's engine processes SEC EDGAR 10-K and 10-Q filings, FRED macroeconomic data, and GDELT news sentiment to generate independent fair value estimates daily.

EVLV currently trades at $6.45 with a QOC of 7.1/10, while FTNT trades at $137.97 with a QOC of 10.0/10.

Both companies are analyzed with models spanning intrinsic (Bayesian DCF, EPV), scenario-based (First Chicago), regime-switching (Markov DDM, RCMH-DCF), machine learning (ML-RIV, FTNN Topology), and ensemble methods (CUCE).