We build for growing companies that have outgrown the way they run — where manual work quietly caps what the team can deliver.
Revenue is up, so you hire again. Each new seat spends its week on data entry, chasing approvals and rebuilding the same report a system should produce on its own.
The same information typed out of an inbox, into a CRM, into a spreadsheet. Experienced people on senior salaries, spending their mornings producing nothing new.
A CRM used as a contact list. A project tool nobody opens. The tools were never the problem — nobody ever mapped them onto how the business actually works.
Your data sits in a CRM, an inbox, a shared drive and three apps that never speak to each other. What you need first is a plan, not another subscription.
Indicative ranges from our own audits — replaced with your measured numbers in the first two days.
We find where your business loses time and money, capture exactly how it runs today, then build the systems that run it for you.
We find where your business loses time and money.
We map your operation end to end — every workflow, every handoff, every bottleneck — and put a cost against each one. You come out with a ranked picture of what to fix first, and what to leave alone.
We capture exactly how your business runs.
Your procedures, tools, data and the unwritten rules that only live in your team’s heads, written down as the knowledge layer your agents run on. This is the part that makes the AI yours instead of generic.
We deploy agents that do the work.
We build on that context, connect the tools you already use, and roll it out beside your team. The repetitive work starts disappearing within weeks, and the system keeps getting better after that.
The repeatable paths through your business, run without a person standing in the middle.
Software colleagues that read, decide and act inside the tools your team already opens.
One orchestration layer above every agent, with permissions, memory and audit.
A clean single source of truth, because an agent is only as good as what it can read.
We meet the stack you already run instead of asking the company to move house.
An automation is a product, not a project. It needs an owner after launch day.
One AI operating system, trained on how your business actually runs: a team of specialist agents covering revenue, marketing, finance and operations in the background — with your people still holding the decisions that matter.
Any action above a limit you set waits for a person. The limit moves as the system earns your trust, never before.
Every read, decision and write is recorded with what it saw. Answering “why did it do that” takes seconds, not a week.
Each agent gets the narrowest access that does its job — granted, reviewed and revoked like any other employee.
Representative structure — yours is shaped around your departments and your workload.
Five stages, each with a fixed length and something concrete at the end of it. You know what is happening this week, what it costs, and what you are holding when it finishes.
We spend two days inside your operation: watching how the work really flows, counting the handoffs, and putting a number on every delay. You finish the week with a ranked list of what to automate first — and, just as usefully, what we would advise you leave alone.
Nothing exotic — these are the tasks somebody in your company is doing by hand this morning. Here is what each one looks like once an agent owns it.
A request lands in a shared inbox. Someone reads it, digs through old jobs to find something similar, rebuilds the scope by hand, then waits on a manager to approve the price. Nine days is normal, and some prospects have already bought elsewhere.
An agent reads the request, pulls the three closest jobs you have already delivered, drafts the scope and prices it off your rate card, then sends one approval to the manager’s phone. The client has a real quote the same afternoon.
HubSpot · Google Workspace · Slack
“Where is my order?”, return requests and address changes all queue behind the same six people, dealt with in the order they arrived rather than the order that matters. Anything sent after 6pm waits until morning.
An agent looks up the order, answers or makes the change itself, and passes on only the cases that genuinely need a human decision — with the history already summarised. Customers get a reply in under a minute, at 2am included.
Zendesk · Shopify · ShipStation
Supplier invoices arrive as PDF attachments and get typed into the accounting system by hand, line by line. Anything that does not match the order surfaces at month end, weeks after the person who typed it moved on.
Each invoice is read the moment it arrives, checked line by line against the purchase order, and posted. Only real disagreements reach a person, with the difference already highlighted and the supplier email attached.
SAP Business One · Outlook · SharePoint
Sector-level examples — swapped for named client results once approvals are in.
At these numbers it pays for itself in 1 months, then keeps returning €0 a year.
Pressure-test this with us→Straight-line estimate. 52 working weeks, no ramp-up discount applied — the Signal phase replaces it with measured figures.
We plug into the software you already pay for and automate the work that happens inside it. Your team keeps its logins, its habits and its workflows — it just stops doing the manual parts. No migration project, no new seat licences, no third system to keep in sync.
Running something niche or homegrown? If it has an API or an inbox, an agent can work it — we’ll map it on the call.
From a single workflow to a full AI operating system. Four ways to deploy Dephrast, with the price agreed before anything starts.
One high-impact workflow, redesigned and automated end to end.
Production AI agents built around one function of your business.
A continuously evolving AI operating layer for your business.
Company-wide AI transformation, with governance, security and scale.
Start small. Prove the value. Then expand across the business.
Clear scope, transparent pricing, results you can measure — and a partner who is still here after launch.
Composite quotes drawn from debriefs — to be replaced with named, attributed client voices.
“We stopped arguing about whether to hire two more coordinators. The question just went away.”
“The approval queue was the thing that sold it internally. Nobody felt replaced, everybody felt faster.”
“Second workflow took nine days instead of five weeks, because the plumbing was already there.”
No. That is the point. We build against the CRM, helpdesk, spreadsheets and inboxes you already run. If something genuinely cannot be automated where it stands, we tell you in the Blueprint rather than after the invoice.
In your cloud, under your accounts, in the region you specify. We deploy into your infrastructure by default. Where a model provider is involved, we use zero-retention endpoints and document exactly what leaves your perimeter.
It gets caught by a gate, not by a customer. Every agent ships with confidence thresholds, a bounded set of actions, and a human approval step on anything consequential. Every decision is logged with its inputs, so a wrong call is traceable and fixable the same day.
Two days to a measured picture of where the time goes. Two to six weeks to a first agent running in production. We deliberately start with one workflow, because a narrow thing that works beats a broad thing that nearly does.
You do. Code, prompts, configuration and documentation sit in your repositories from the first commit. If you end the engagement, nothing switches off and nothing needs re-buying.
One decision-maker who can say yes, and a few hours from the people who actually run the process. No internal project team, no six-week discovery. We work around your calendar, not the other way round.
Give us thirty minutes. We will walk through how your operation runs today, show you where AI takes real work off your team, and leave you with a clear roadmap — whether or not we are the ones who build it.
