Automation · workflows, processes, enablement
Every business has jobs that run on copy-paste, spreadsheets, and someone remembering to check on Friday. We find them, work out which are worth automating, and build those. Some of it needs AI. Plenty of it does not, and we will say so.
Custom scope · Written quote first · We start with the process, not the tool
Why_this_exists >>
01_The_shift
hours a year, for the average knowledge worker, lost to duplicated work — over five working weeks. Work that used to need a developer and a six-month project can now be done in a fortnight, so the list of things worth automating got much longer almost overnight. Most companies have not been back to look at their list since. Asana, Anatomy of Work Index — 10,000+ knowledge workers
02_The_gap
The failures we get called in to fix are rarely technical. Someone automated a workflow nobody had mapped, with nothing written for the exceptions that actually matter, and now it fails quietly at ten times the volume. Automating a broken process just breaks it faster.
Automate the process, not the symptom.
We map how the work actually happens rather than how the process document says it happens, then automate the parts that survive the comparison.
What_we_do
We build on whichever automation platform fits the job, including licences you already pay for. Most of the work is joining systems that were never designed to talk to each other. If your tool has an API, it is usually a question of scope rather than whether it is possible.
agents · steps · approvals
Multi-step work handed to agents that check in with a person at the points where a mistake costs you something. The rest runs without anyone watching it.
map · build · handover
The recurring manual work that eats your team's week. We map how it actually runs, exceptions included, then automate what survives. The cheapest thing that works is frequently not the AI one.
tools · rules · training
Your team is already using AI, usually by pasting company data into a chatbot nobody approved. We replace that with tools you have chosen and rules people can actually follow.
prototype · answer · costing
You have an idea and no way to know whether it is worth funding. We build a small real version in weeks rather than quarters, and tell you honestly what we found.
Connects to: JIRA SLACK MICROSOFT 365 GOOGLE WORKSPACE SALESFORCE HUBSPOT SERVICENOW ZENDESK WORKDAY NETSUITE SAP DOCUSIGN AND MORE
How_it_works
Who_it's_for
ops · finance · back office
Invoice matching, onboarding, reporting, moving data between two systems that will never talk to each other. It all works. It also costs you a person's week, every week.
AI adoption · enablement
The licences went out. A few people use it well, everyone else pastes things into a chatbot and hopes. We close the gap between the tool and an actual working habit.
proof of concept · evaluation
You need to know whether an idea works before funding it properly. We build a small real version of it and give you an honest answer, including when the answer is no.
Pricing
Automation work depends entirely on the process behind it, so this is scoped per engagement rather than sold in tiers.
Let's scope it
We map how the work actually happens and tell you what is worth automating.
Most common
Let's scope it
We build the automation, document it, and hand it to your team.
Final pricing depends on scope and is confirmed in a written quotation before any commitment.
FAQ
No, and we will tell you when it should not. Plenty of what we build is a scheduled script, a fixed integration, or a better configuration of a tool you already pay for.
AI earns its place when the work involves judgement or messy text: reading a supplier email that never looks the same twice, sorting requests that do not fit clean categories, drafting something a person will check. It does not when the work is moving a number between two systems on a schedule — that is a job for code that does the same thing every time.
The distinction is commercial, not ideological. An AI step carries a cost per run, a latency cost, and a small chance of being wrong. Where a deterministic script does the job, it is cheaper, faster, and far easier for your own team to maintain after we have gone.
A multi-step process handed to an AI agent that works out how to complete it, rather than following a fixed script. It is worth it when the steps genuinely vary case by case. We build them with a human check at whichever points would be expensive to get wrong.
A fixed workflow knows the order in advance: do this, then that, then stop. An agentic one is given a goal and the tools to reach it, and chooses the order itself. That flexibility is the whole point, and it is also the risk — the same freedom that handles the unusual case can take an unusual route through your systems.
So the useful question is not whether to use one, but where the checkpoints go. Anything irreversible, anything a customer sees, and anything that spends money is worth a person confirming.
It depends on the shape of the work, and the honest answer is a range rather than a number.
With a clear scope, small pieces land quickly. A notification to Slack or email when something happens on your platform is usually a day. Automating a full purchase flow is not — the work there is in exercising every path it can take, including the ones nobody thinks about until they break in front of a customer.
The biggest factor is what already exists: a mature system that needs one more piece is faster than a greenfield build that needs all of it. The second biggest is you. The more you can tell us about the product, the people using it and what a good outcome looks like, the less of the estimate is guesswork.
A process audit is usually a couple of weeks, and you get a written estimate before committing to a build. We do not quote a price without a scope — a number without one is a number that changes later.
Getting your team genuinely using AI in their real work, with clear rules about what goes into which tool. Most companies bought the licences already and have very little to show for them.
The gap is rarely enthusiasm. People do not know which of their own tasks are a good fit, they are unsure what they are allowed to paste into a chat window, and nobody has shown them what good looks like in their job rather than in a demo.
So the work is specific: find the tasks in each team where it genuinely helps, write down what may and may not be shared, and get people using it on those tasks until it is habit. The measure is whether anyone still does it the old way afterwards.
It will eventually — a supplier changes a form, or a system changes an API. We build in monitoring so you find out immediately instead of at quarter end, and we document it so your own team can fix it.
Silent failure is the real danger with automation. A person who stops doing a task notices. A script that stops doing it does not, and the gap surfaces weeks later when someone asks why the numbers do not add up. So anything we build reports that it ran, and says so loudly when it did not.
Documentation is the other half. You get the why as well as the what: which systems it talks to, what it assumes, and where to look first when it stops. Ongoing support is available, but we do not assume you want it — being unable to leave us is not a feature.
Get_started >>
Tell us what is taking your team's time. We reply with next steps, usually a short call followed by a written quote.
Prefer email? Write to info@kryo.solutions