Stop paying $80,000 a year for work AI does for $2,000.
Connect your tools and see who AI can already replace on your team.
You set it up yourself. No one from your team has to be involved.
Your data stays secure and is never used to train models. SOC 2 audit in progress. GDPR ready.
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Your biggest line of burn is people, but you cannot see who is doing work that AI already handles for the cost of tokens.
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Figuring it out normally takes interviews and audits, with sign-off from a team that has no interest in optimizing itself away.
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So you keep paying $80,000 a year for a process an agent runs for about $2,000 a year.
Extend your runway without slowing the product down
Three to four months of runway is the difference between making the round and shutting down. One replaced employee on routine work puts $80,000 a year back into your runway. Replace three and you have bought yourself another quarter, at the same delivery speed.
- Same delivery speed with a smaller team
- A clear view of where your payroll actually goes
- You make the call, with no approvals and no internal sabotage
Hit your OPEX target with numbers, not guesswork
You have been handed a 20 percent team-cost target. Usually that is blind and painful. Here you see the unit economics of every process: $80,000 a year by a human versus about $2,000 a year by an agent. The efficiency goal closes as concrete line items.
- CFOpredictable payroll reduction with clear per-process economics
- COO / Headsroadmap delivered by a smaller team, higher output per person
- Boardevery "replace or keep" decision is justified, with no black box in front of them
You connect it yourself.
Slack or Teams, your task tracker, your meetings. You do not need to involve anyone from your team, and there is nothing to roll out to them. The person responsible for costs sets it up alone.
It builds a process map.
From the signals in your data, the assistant maps real processes: who, what, how often, how much time, and how much money each one costs.
Replaceable versus critical.
You see which process to hand to AI and which person not to touch, and why.
Optional: turn the map into agents.
When you are ready, upload the same map into an agent layer, and the routine processes on it become working agents right away, ready to start delivering the work.
The math, in dollars.
| Metric | By a human | By an AI agent |
|---|---|---|
| Routine process | $80,000 / yr | about $2,000 / yr in tokens |
| Speed | hours to days | minutes |
| Availability | one seat, working hours | 24/7, scales |
We do not compete with other software. We compete with your payroll. That is a 40x gap, and you see it in the very first map.
We do not cut blindly.
The assistant keeps the people who:
are critical to the business and hold key processes together
carry unique knowledge the map reveals, like elite sales or negotiation skill nobody else has
drive AI themselves by using and configuring the agents
And it spends sensible AI money: the goal is to deliver a meaningful result, not to burn tokens. Every agent is tied to a process with measurable output.
Why Headcount Copilot
Self-serve, no team needed.
Run by the person accountable for costs.
Map built on real data, not interviews.
We show how things actually are.
Not just a report, a working replacement.
You can get agents, not only a slide deck.
Every decision is in dollars
and justified.
Your data stays secure.
Never used to train models. SOC 2 audit in progress, GDPR ready.
See how much payroll you are paying for work AI already does
You connect it yourself. No one from your team has to be involved.