AI is easy to buy.
Trusting it is the hard part.

Most AI problems are not model problems. They are ownership, evaluation, and workflow problems that show up after the demo works. Joust helps companies figure out which situation they're actually in, and fixes the specific thing that's stalling them, without selling a platform or locking you into ours.

Six situations we see most often. If one sounds like yours, that's the conversation to have.

You bought or built AI agents and don't know if they're actually working

Nobody defined what "good" looks like before it shipped, so there's no way to catch it quietly failing. We help you write down what good actually means for that specific agent, then measure against it.

You're being pitched constantly and can't tell real capability from a good demo

The vendor language all sounds the same, and the ROI slides never show adoption or quality numbers, only the upside case. We give proposals an honest, buyer-side read before you sign.

You have pilots running but nothing to show the board in dollars

Activity is happening, agents exist, dashboards show cost, but nobody can say what any of it is actually worth. We size the real opportunity and sequence it with numbers attached.

Something is running in production and nobody owns it

It works today, but there's no one accountable for what happens when it breaks, no logging, no rollback plan. We harden what already exists so it can be trusted, not just demoed.

Your team knows how the work really happens, and that knowledge isn't in a system anywhere

It leaves when they do. We help capture what your best people know into something the company actually owns.

You don't have a senior technical voice in the room for AI decisions

The calls are being made by whoever is in the meeting, not by someone who has to live with the result. We can be that voice, for a stretch or on an ongoing basis.

Where do you
actually stand?

Most companies rate themselves one stage ahead of where the evidence puts them. If any of the above sounds familiar, the fastest way to find out which one is real for you is a conversation, not a form. Get in touch and describe the workflow or the problem; we'll tell you plainly where it sits and what we'd do about it.

Most operations move through five stages: Ad hoc, using AI in scattered one-off ways; Experimenting, running pilots to see what sticks; then the production gap, where demos work but nothing is trusted in daily use; Operationalized, where a few workflows run reliably with owners and guardrails; and Intelligence-first, where the systems compound because the company owns the data, the evaluation, and the judgment around them. Place yourself honestly, then let's talk about the next step.

Estimate what manual
work is costing you.

Plug in your real numbers and get an estimate in under 2 minutes, something concrete you can bring to a conversation. Nothing you enter is captured for leads, and nobody from Joust will contact you unless you ask.

1
Company
2
Departments
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Parameters
4
Results

About Your Company

Help us understand your organization so we can project realistic savings.

$
$/yr

Department Breakdown

How many people on each team, and what % of their time goes to repetitive tasks?

35%
40%
45%
50%
40%
45%

Investment Parameters

Defaults are based on industry benchmarks. Adjust if you have specific numbers.

40%
$/yr
$

Projected ROI

Your AI Automation Opportunity

-
Annual Savings
-
Payback Period
-
3-Year ROI

Hours & Capacity

Annual Hours-
Equiv. FTEs-

Investment

Year 1 Net-
Year 2+ Net-

Savings by Department

DepartmentTeamHoursSavings

By Department

Department savings chart

3-Year Cumulative

3-year cumulative chart

Before vs. After: Hours on Repetitive Tasks

Before vs after chart
Methodology & Assumptions

Savings are calculated based on recaptured hours from automating repetitive tasks. Hourly cost is derived from the fully loaded annual cost divided by 2,080 working hours per year. The automation capture rate represents a conservative estimate of what percentage of identified repetitive work can be effectively automated with current AI tools. Savings projections use a ramped adoption model: Year 1 captures 60%, Year 2 reaches 85%, Year 3 hits 100%. Year 1 costs include implementation and annual tooling. Year 2+ costs include only annual tooling. Actual results may vary based on process complexity, data readiness, and implementation quality.

Ready to validate these numbers?

Book a 30-minute call to validate these projections against your actual workflows.

Tell us where you're stuck.

Describe the workflow or the problem, and we'll reach out within 1 business day to tell you plainly where it sits and what we'd do about it.

Get in touch