The honest answers.
The model is unusual, so the questions are fair. Here’s where we don’t hedge.
This sounds too good to be true. What’s the catch?
Three honest ones. First, we only take on processes where we’re confident in the projection, so we say no a lot; if a process is too messy or too small to measure cleanly, we won’t pitch it. Second, the shortfall refund requires that the system was actually used as set out in the agreed scope, so we’re measuring the automation and not a process that quietly went back to the old way. Third, we’re a young firm still building a public track record, which is exactly why the risk sits with us and not you: the guarantee stands in for the years of case studies we don’t have yet. You can check who we are on our about page and register entry, and on LinkedIn.
Are your case studies real?
Every asset carries three independent labels. System status says whether it is a concept, a demo-tested system, or deployed. Data status says whether the inputs are illustrative, synthetic, anonymized real data, or client-approved. Outcome status says whether savings are modeled, observed, or client-verified. The current demo outputs come from runnable systems on synthetic data; they are not client outcomes.
How do you define and measure “savings”?
Before we build, we agree a baseline together: the labor hours your team spends on the process times their loaded cost, plus any tool licenses we’ll replace and the cost of errors and rework. From that we set a projected Year-1 saving and write it into the scope. After launch we re-measure the same line items, so the number is transparent and mutual the whole way through.
What if the savings come in smaller than expected?
Then we correct the fee. If projected savings were $40,000, the delivery fee would be $20,000. If verified savings later came to $30,000, the corrected fee would be $15,000 and we would refund $5,000. The system has to have been used as set out in the agreed scope, so we are measuring the automation rather than a process that quietly returned to the old way.
When and how do we pay?
There’s nothing to pay upfront. The fee, 50% of the projected Year-1 saving, is due when we deliver the working system. If you’d rather not pay it in one go, we can spread it over the first three months as the automation ramps up. After that, maintenance is free for a year.
Who owns the automation you build?
You do. The system, the workflows, and the configuration are yours. We document it so you’re never locked in, and the included maintenance is a service we provide on top of something you already own.
What happens after the first 12 months?
Maintenance is free for the first year. From month 13 it moves to a flat 10% of the annual savings, which covers ongoing upkeep and optimization. At month 6 we also run a free upgrade review: if a better tool or model has appeared that would improve your system, we re-platform you at no charge.
How fast can you build something?
Most first automations are working in 5 to 10 days, not months. We deliberately scope the first build narrow, around one painful, costly process, so you see real output quickly. Speed is part of the model: the sooner it runs, the sooner the savings start.
Is our data safe? Are you compliant?
We build on your tools and your accounts wherever possible, so you keep control of the systems. See.ke is operated by Seeke LLC, a Wyoming company. Before any workflow touches personal data or production, the scope covers permissions, retention, data location, subprocessors, security controls, and any required data-processing terms.
Why would an agency price it this way?
Because building software got cheap and we’re fast at it. When the build cost is low, pricing against the value created beats billing for hours, for both sides. Tying our fee to your savings, and backing it with a refund, keeps us pointed at work that actually pays off instead of billable busywork.
Still have a question? Ask it on the fit call.
It’s free, it’s 20 minutes, and qualified processes move to a measured audit.