We shadow the actual work before designing anything, counting how often the same number gets typed into a second system
That is why our estimates hold, and why we sometimes say a process should be redesigned rather than automated
Automating a bad process only makes it fail faster
Every process has cases that break the rules, and they are where automation projects quietly die
We define what the system handles, what it escalates, and what the person picking up an escalation actually sees
Corrections feed back in, so the exception rate falls instead of staying where it started
We instrument the current process before touching it, so the improvement is a number rather than a claim
If the automation is not paying for itself you find out on the first process, not after committing to a programme
Teams that automate five things at once tend to finish none of them
Froggik
"DESH Team maintained effective communication throughout the project."
Thanks to DESH Team's work, the client saw increased product recognition within the cryptocurrency community. The team managed the...
Viktoriia Bernatska
Co-Founder
ChainCrafters
"I liked their corporate policy and how they turned to customers and their wishes."
DESH Team delivered the project on time, effectively improving the site's UX and flow. The team took the time to understand the cl...
Kolya Vovkun
CEO, Founder
Dropshipping
"I really like how they treat their clients."
DESH Team successfully completed all deliverables; the branding was a great fit for the client's company, and the website was done...
Tetyana Yarchak
CEO
High volume, rule heavy, currently done by copy and paste. Discovery ranks your processes by hours consumed and error rate, and we automate the top one end to end before touching the second. If your top process turns out to be a bad process, we will say so.
In the projects we have run it removed the part of the job nobody wanted. The common pattern is the same headcount handling two to three times the volume. If your goal is headcount reduction, say so at the start, because it changes what we build and how we phase it.
It is the normal starting condition and part of the work. Cleaning and validation get built into the pipeline. Where the data genuinely cannot support what you want, you hear that during discovery rather than after three months of building.
A single process typically goes live in four to eight weeks, including a review period where a person still checks every output. Rollout across several processes runs in phases after that, each starting once the previous has held for a month.
Rules and prompts live in configuration your team can edit, with documentation handed over. Structural changes need us or your developers. We aim for the boring version where a threshold change does not require a deployment.
