ROI & cost savings
What it saves you, with the math shown
Security spend is easy to justify with fear and hard to justify with numbers. These are the numbers. An interactive model you can set to your own reality, and four scenarios, one per product, with the assumptions stated out loud. No audited guarantees here, just the shape of the saving and how we got to it.
Model your own stack
The two savings almost every team can name: the point tools a platform consolidates, and the analyst hours that verification gives back by removing false positives. Drag the inputs to match your world.
How to read this. Consolidation shows the gross point-tool spend a single platform can replace; the platform has its own cost, which offsets part of it, so treat it as a ceiling, not a check. Analyst value assumes verification removes the share of false positives you set, freeing that triage time. The model is deliberately simple and transparent so you can defend it, or argue with it, in a budget meeting.
Four scenarios, four products
Shield
Consolidate the mid-market security stack
TodayA team stitches together an ADR tool (~$30K), API security (~$100K), protective DNS (~$15K), and a SIEM tier (~$60K). Call it ~$205K/yr across four contracts, four integrations, and the SecOps hours spent correlating four consoles by hand.
With NemesisOne platform, four engines, one correlation brain. Per-tenant baselines, cross-layer correlation, and compliance built in, priced for the mid-market instead of four six-figure contracts.
What you saveThe overlap and integration tax, plus the analyst hours lost stitching alerts from four tools into one incident. A six-figure line-item reduction is a realistic target, on top of recovered analyst time.
Figures are directional list-price estimates. Your stack and negotiated pricing will differ.
The thinking behind it →Red
Continuous verified testing vs. episodic pentests
TodayTwo to four external penetration tests a year at ~$20K–$40K each, every one a point-in-time snapshot, plus internal hours triaging scanner output in the ten months between them.
With NemesisContinuous, autonomous, proof-gated testing. Only verified findings reach a report, so triage collapses, and coverage never lapses between engagements.
What you saveThe per-engagement fees you can retire or redirect, and most of the triage time an unverified scanner would cost. The larger value is risk: a vulnerability caught in week three instead of month eleven.
Autonomous testing complements, and does not fully replace, a skilled human red team for the hardest targets.
The thinking behind it →Blue
Driverless EDR and the price of an outage
TodayA kernel-driver EDR whose worst case is a fleet-wide outage (the July 2024 lesson). One bad update across 2,000 endpoints, down four hours at a loaded cost per endpoint-hour, gets large fast, and that is before ransomware downtime when detection misses.
With NemesisA driverless agent that fails without taking the host down, plus deterministic rollback that turns a missed ransomware event into minutes of recovery instead of days.
What you saveThe tail risk of a correlated outage and the downtime of a slow ransomware recovery. This is avoided-loss, not a line item, and it is the expensive kind.
Avoided-loss depends on your endpoint count, downtime cost, and threat exposure. Model it with your numbers.
The thinking behind it →Forge
The cost of unverified vulnerability reports
TodayA team fields vulnerability reports, internal and, increasingly, AI-generated, each costing an analyst an hour or more to reproduce or disprove. At volume, that is a full-time role spent on maybes.
With NemesisEvery finding ships with a reproducible proof a human checks in minutes, and a clean run reports nothing. The engine respects the maintainer's inbox instead of flooding it.
What you saveThe analyst hours lost disproving false reports, and the far larger cost of a real bug dismissed in the noise, plus the value of finding a flaw in your dependencies before an attacker does.
Discovery depth depends on the target. Forge reports the highest rung it can prove, and downgrades honestly.
The thinking behind it →The honest version of ROI is a model you can change, not a number we picked. Bring your own inputs, and if the math does not hold up for your situation, we would rather you know that before you buy.