An AI seat rightsizing agent reviews how each seat is used and groups people by behaviour, such as heavy, light and occasional users.
Reads seat counts, plan tiers and feature use for one tool.
Sorts users into heavy, light and idle groups.
Checks which users only touch features in a lower plan.
Writes a recommended seat count and tier mix with reasons.
The buyer accepts, edits or rejects the proposal.
Stores the agreed mix for the renewal conversation.
It proposes a target mix, for example fewer premium seats and more standard ones, along with the effect on the renewal quote when the pricing is known from the contract.
It also watches for the opposite problem. Teams that are growing past their seat count get an early flag so they can add seats on agreed terms rather than at list price.
A single seat count hides the fact that people use the same tool very differently, and tiers are priced in steps that are easy to misjudge.
Heavy features sit in the top tier, so a few power users can force many light users onto a plan they do not need.
Minimum commitments, true-up clauses and co-terming rules decide whether a smaller number of seats saves anything.
Headcount moves between renewals, so the right number last year is not the right number now.
Without usage data by tier, there is little to bring to the negotiation.
Capture the current tiers, seat counts and per-seat rates from the contract and order form.
Group users by how much they use the product and which features they touch.
Test alternative seat and tier combinations against the contract's minimums and step pricing.
Flag clauses that restrict reductions, such as a mid-term commitment or a notice period.
Write two or three options for the owner with assumptions stated and the data behind each.
Bring a small sample and watch Flo work through it.
| Aspect | By hand | With the agent |
|---|---|---|
| Scope | Rightsizing is checked on the biggest tools only. | Every application with usable data gets the same comparison. |
| Tier fit | Plan levels are compared by reading vendor pricing pages. | Users are matched to the lowest tier that covers the features they use. |
| Growth | Headcount plans are forgotten when seats are cut. | Planned joiners can be added so the proposal does not undershoot. |
| Negotiation | Buyers walk into renewals with a rough guess. | Buyers arrive with a usage-backed seat and tier proposal. |
| Repeatability | Findings sit in one person's spreadsheet. | Each proposal and decision is kept for the next renewal. |
| If | Then | Who decides |
|---|---|---|
| Most users only touch features in a lower tier | Propose a mixed-tier seat plan with the features listed | Buyer and application owner |
| Heavy users sit on a tier too low for their needs | Flag them for an upgrade review | Application owner |
| The contract sets a minimum seat count | Show the minimum beside the proposal and cap savings at it | Buyer |
| Hiring is planned in the same team | Keep a buffer of seats and note the assumption | Team lead confirms |
| Usage is seasonal for a team | Show peak and quiet periods side by side | Application owner |
| The vendor prices per tier in bands | Check whether a seat change crosses a band | Buyer reviews |
Some premium features are not logged by the vendor, so low use may be a data gap. The agent states what is unmeasured and asks the owner before proposing a downgrade.
A senior user may log in rarely but is the reason the tool was bought. The owner marks such seats as protected so they are never proposed for downgrade.
Some contracts only allow seat changes at renewal. The agent holds the proposal until the next window and tells the buyer the date.
A team move can change who needs the tool. The agent flags a sharp change and asks the owner to confirm before updating the proposal.
Talk it through with the team. We will map it to your steps and show where a person stays in control.
Run the agent on one multi-tier tool and compare its proposal with what the buyer would have chosen.
Record where feature data was missing and what owners overrode.
Create the rule for sponsor and admin seats, then include more tools.
Generate proposals ahead of each renewal and keep sign-off with the buyer.
A higher figure means seats and tiers match how people work. Read it with the headroom you have kept for growth, since a perfect fit with no spare seats is its own risk.
Quick answers to what people ask most about seat rightsizing.
Book a demoIt is matching the number and tier of paid seats to real usage. It can mean fewer seats, a lower tier for some users, or more seats where a team has outgrown its plan.
Unused license detection looks for seats with no activity. Rightsizing looks at active seats too and asks whether they are on the correct tier and in the correct quantity.
Not necessarily. Contract minimums can block reductions, and a growing team may need more seats. The agent shows the effect under each option so people can decide.
Ideally well ahead of the renewal notice window, so there is time to model options and negotiate. Many teams also review mid-term after large hiring or restructuring changes.
Unused license detection is the practice of finding paid software seats that are assigned but not being used.
→A SaaS security review is a check of whether a software vendor's security practices and data handling meet your requirements before or after purchase.
→License optimization is the adjustment of licence types, tiers, counts and plans so they match how software is actually used.
→SaaS offboarding is removing a departing person's access, or retiring a whole application, so seats, data and costs are closed out properly.
→Bring a small sample of real items. We will show what Flo handles on its own and where it hands over to your team.
