Estimate the operational and financial impact of deploying autonomous AI agent teams across your organisation.
Built using conservative operational benchmarks and human-in-the-loop deployment assumptions. Adjust the inputs to model your reality.
Modelling stance
— pick the assumption set you want to defend to your CFORealistic deployment assumptions for a typical 12-month rollout.
Your operating context
Count only people actually executing these workflows, not your whole company.
Salary + benefits + overhead. $55/hr ≈ $95K/yr fully loaded.
Used to estimate revenue acceleration — kept conservative via scenario weighting.
Workflows to assess
Each workflow has an oversight requirement; the model never assumes full hands-off automation.
Nagent platform pricing
Per-function, scales with the operating-team size. Cost grows in line with adoption — never per-seat-flat.
Founders
from $300/mo per function
Up to 25 operators · standard governance · 1–2 functions
Growing
from $649/mo per function
26–100 operators · multi-agent debates · 2–4 functions
Enterprise
from $999/mo per function
100+ operators · full Topology · Private Cloud option
Your estimated platform cost
Founders tier · 4 functions
Final pricing for Enterprise + Private Cloud is configured during onboarding; this estimate matches our standard published rate.
Estimated annual business impact
$154,514
labor efficiency + revenue acceleration
Expected ROI
974%
2 mo payback
Operational efficiency
1,902 hrs
/ year reallocated
8%
workflow absorbed
1.1×
faster cycles
Financial impact
AI operating cost / yr
$14,386
Recommended AI agent stack
Your future operating model
Outbound prospecting
covers: Lead qualification & outbound, Market & account research
Analytics + reporting
covers: Reporting & analytics, Market & account research
Lead qualification
covers: Lead qualification & outbound
Content production
covers: Content production & copywriting
Voice + tone QA
covers: Content production & copywriting
8%
Operational coverage
Moderate
Oversight required
43/100
Deployment readiness
Organisations deploying autonomous operations typically reduce execution bottlenecks by 35–50% within 12 months. AI-native operating teams execute campaigns and research cycles roughly 2× faster with the same headcount, freeing the saved capacity for higher-leverage work.
Estimates are based on conservative deployment benchmarks from organisations implementing human-supervised autonomous AI workflows.
Actual results vary based on workflow maturity, integration depth, and adoption pace. Nagent agents operate with human-in-the-loop oversight by default.