We design and build the agents that do the busywork, so your team spends its hours on the parts that need a human.
Six things, done properly and wired into the tools you already run. No platform to adopt. The work lives where it already happens.
Hand-offs, approvals and follow-ups that currently need someone to remember them. We connect the steps so records move, notifications fire and nothing falls between two inboxes. n8n · Make · Zapier · custom services
Agents that read, decide and act inside your systems: triaging a ticket, drafting the first reply, updating the right field, and knowing when to hand back to a person. Claude · retrieval · tool-use · guardrails
Move and clean data between systems on a schedule you can trust. Checks catch the bad rows before they reach a report, and alerts fire when something upstream changes. Postgres · dbt · warehouse loads
The small app your team keeps asking for: a dashboard, a review queue, an admin panel. Built around the actual process, not a spreadsheet held together with hope. web app · dashboards · admin panels
We read your actual bill and usage, cut the idle spend, right-size what's over-provisioned, and set the alerts so a runaway cost never lands as a month-end surprise. AWS · GCP · Azure · cost & usage audits
You invested in AI and the payback is murky. We measure what your models and agents actually return, set the KPIs that matter instead of vanity metrics, and hand you a plain list of what to fix, cut, or double down on. usage & cost audit · KPI framework · optimization roadmap
Most engagements ship a first working automation within two to three weeks. Order matters here: each step depends on the one before it.
We shadow the real process: the clicks, the copy-paste, the exceptions. Then we write down exactly what happens today, edge cases included.
We build the automation against your real tools and data, in small pieces you can see working, so there are no surprises at the end.
It goes live behind a check, running alongside the manual process until the output matches and your team trusts it.
We monitor it, fix what breaks upstream, and improve it as the process changes. You get the logs; we get the pager.
A few representative engagements. Details are generalised, the mechanics are real.
An agent that matches incoming payments to open invoices, flags the genuine mismatches for a human, and books the rest, reading the same PDFs the finance team used to open by hand.
From a full morning of matching to a five-minute review of exceptions.
Inbound support mail is read, categorised and assigned to the right queue with a drafted first reply, so agents open a ticket already halfway answered instead of a blank one.
First response time cut to under an hour, around the clock.
Orders, stock and shipping statuses kept in sync across the store, the warehouse and the finance sheet, with validation that stops a bad export before it becomes a wrong number.
Nightly reconciliation replaced by a live, checked feed.
A single review queue where the team approves, edits and publishes work, replacing a shared spreadsheet, three Slack threads and a lot of “who's got this?”.
One screen instead of four tabs and a guess.
Vedolya is a small automation studio. We don't sell a platform or a licence. We build the specific system your operation needs, wire it into the tools you already trust, and stay on to run it. Automation is only worth it if it keeps working after we leave the room.
The things people ask before they start. If yours isn't here, just ask.
We build software that does your team's repetitive work: reconciling invoices, triaging support tickets, keeping data in sync, running first-pass reports. It plugs into the tools you already use, so nobody has to learn a new platform. We build it, run it, and you own it.
A freelancer builds a flow and moves on. When it breaks upstream, it becomes your problem. We map the real process first, build it properly, then keep it running: monitoring, fixes, and changes as your process evolves. Zapier is one of our tools, not the whole answer.
You own it. Everything runs in your own accounts and infrastructure, on your keys, and you keep the code. There is no Vedolya platform to stay subscribed to. If you ever want to take it fully in-house, you can.
We start with a fixed-price audit of one process, so you see the plan and the expected time saved before committing to more. Then a fixed-price first build, usually two to three weeks. If it works, most clients move to a monthly retainer where we operate and expand it. Pricing tracks scope, and the audit tells you exactly what you're getting.
It runs in your environment, on your credentials. We don't hold your data on a Vedolya server. Agents get least-privilege access and ask a human before doing anything irreversible.
We watch it. When an upstream tool changes or a step fails, we get the alert and fix it, and you get the logs. That is the point of the retainer: automation is only worth it if it keeps working after launch.
The ones you already run. We commonly build with n8n, Make, Zapier, Postgres, dbt, and the major AI models, on AWS, GCP, or Azure. If your stack is unusual, we work with it rather than around it.
