Quotes typed twice into two different systems. New job requests sitting in a shared inbox until somebody gets to them. A report your office manager rebuilds by hand every Monday morning. Designli assigns you a team that automates those jobs one process at a time, starting with whichever one is costing you the most, and you decide what gets taken on next.
Book Your Impact WeekYou have probably seen the demo. Somebody pastes a customer email into a chat window, the AI writes the quote in four seconds, and the room agrees this is going to save everyone a lot of time. Then Tuesday arrives with real customers and real edge cases, and the whole thing quietly goes back to being done by hand.
The gap is hardly ever the model. It is everything the demo quietly skipped on its way to a four-second quote.
That unglamorous half is the work Designli does. When there is no API we write the integration. When the exception lives in someone's head we get it documented. When the output needs a human check we build the screen where that check happens.
Designli's product teams run Hypothesis-Driven Development. Every change ships as a stated bet, with the instrumentation in place to tell you whether the bet paid. It is how we build for companies scaling what they have already built.
So every automation enters with a number attached. How many hours a week the job eats today, how often it goes wrong and what a mistake costs to unwind, and what the whole thing should cost once software is doing it.
Those numbers get written down before anyone builds anything, because they are how you will know a month later whether it worked.
Your pod works one process at a time, in the order you agree to, and repeats these four steps on each one. Nothing gets built before step one is finished, because a process nobody has priced is a project nobody can judge.
We pick one process and pin down what it costs you today: hours a week, who spends them, where it breaks, and what an error costs to unwind. That number is what the build gets measured against.
The first cut lives inside the tools your team already opens every day, so nobody has to learn a new system to get the benefit. A narrow automation running next week teaches you more than an ambitious one still in review.
For the first stretch, the automation and the person doing that job today both run, and we compare the two outputs. Every disagreement gets fixed in the software before anyone is asked to rely on it.
You get documentation, a named owner on your side, and a walkthrough of how to switch it off. Then you choose which process your pod takes on next.
You get a team assigned to your business, sitting inside how you work rather than picking up tickets from a queue. Your pod pairs a full-stack engineer with a business process consultant who owns the workflow side, led by a Designli pod lead who has run this loop before.
You pay for their assigned time, and you decide what they point it at. The backlog of processes belongs to you, so when a new bottleneck jumps the queue, you say so at the next check-in and that becomes the work. Cancel any time on 30 days' notice.
Everything your pod builds is yours. Custom code in your repositories, running on your cloud and model accounts, with the prompts and the documentation handed over as they are written. Two things follow from that:
Repositories, accounts, API keys, and the automations themselves are in your name from the first week. Nothing sits underneath them that Designli has to keep licensing to you.
Each automation ships with a plain description of what it does, what it is allowed to touch, and how to turn it off. Your ops lead can hand that to a new hire or to another firm.
Four kinds of work, run by the same engineering practice behind everything else on our services list. Most engagements spend the bulk of their time in the middle two, because that is where the manual hours usually sit.
We inventory the work your team does by hand, score every process on hours, error rate, and effort to automate, then give you an ordered plan. You come out knowing the three things to do first and the ones to leave alone.
Intake that files itself instead of waiting in an inbox, scheduling that stops living in a spreadsheet, invoicing generated from the job record, and reporting nobody has to reassemble. This is where most of the recovered hours come from.
Agents that read an incoming document and pull out the fields your team would otherwise re-key, draft the follow-up email, and route a quote request to the right person. They are built with scoped permissions and an audit trail, so you can see every action one took and why.
If you also sell software, we add the AI features your customers will actually use: document extraction, search across your own content, drafting and summarizing inside the screens they already work in. These are built on hosted models through their APIs, on top of the product you have.
Your team walks us through the work they do. We find where effort is going into something software could now carry, and we price it.
Scored findings report. Your processes ranked by hours, error rate, and effort to automate.
Customized 90-day automation plan. Sequenced, with a named first build.
Written Day-30 outcome. Hit it, or your next month is free.
Automation earns its way in by being boring and reversible. Every agent Designli builds is scoped, logged, and owned by a named person on your team.
Anything that spends money, commits your company, or goes out to a customer stops for human approval first. The AI does the preparing, and a person does the releasing.
Each agent gets its own credentials and only the access its job requires, reviewed the way you would review what a new employee can open. That access is logged, and every action the agent takes is recorded.
Every automation has a named owner on your side and written documentation of what it touches. Turning it off is one clear step that does not require calling us.
Ask Tyler Morton, our account executive. Thirty minutes, one process, and a straight answer about whether software should touch it at all.
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CEO Jeff Davison reports about a 30% increase in feature enhancements, and a backend Designli rebuilt so the platform can reach the scale he is after.
They have a very good process for gathering feedback from multiple stake-holders, a great [process] to get clarity around a new solution.
The ultimate mission was to build an AI-driven, two-sided marketplace that ethically connects diverse patients to clinical trials. […] The proficiency demonstrated in organizational execution and the subsequent successful generation of a conceptual prototype were highly commendable.
For technologies, we're using non-generative AI and computer vision technologies with multi-modal components.
Give us 30 minutes and walk us through a job your people still do by hand. We will tell you whether it is an automation, a settings change, or something worth leaving alone, and what an Impact Week would dig into first.
