Built by people who spent twelve years inside the industry, in more than thirty countries. Pick your operation and watch one day.
Fourteen kinds of operation. One AI backbone underneath.
Press play, or drag the day. Watch the left side when something breaks.
People don't trust AI in waste because AI doesn't know waste. Here's the difference when something actually happens in your operation.
Not modules. Not dashboards. Work that used to need a person, done by an AI that understands the operation it is working in.
Customers, drivers, suppliers — the AI works in the channels your people already use. Watch three conversations from this morning.
A waste company is trucks and bins. It is also a payroll, a ledger, a stock room, a supplier list and a filing cabinet. One backbone runs through the building: the same AI that handles the 06:12 breakdown runs the invoices, the rosters and the stock room, with the same rule. It does the routine, and it asks you about money.
Routes, rounds, positions, exceptions. The day you just watched. This is where it starts, because this is where the money is made and lost.
Timesheets from in-cab data, not memory. Overtime and agency hours reconciled. Licences, CPC and ADR renewals booked before they lapse. Onboarding packs written, contracts drafted, exits handled cleanly.
Invoices generated from lift and weighbridge records, so nothing is missed and nothing is disputed twice. Supplier invoices matched to tickets. Overdue accounts chased in the right tone. Cash forecast updated every day.
Tyres, fuel, containers, spare parts, disposal capacity. Stock watched against usage, POs drafted from framework prices, supplier prices tracked so a renewal never surprises you. You approve the spend.
Where every container is, who is paying for it, and which ones have gone missing. Vehicle maintenance on hours and faults, not on the calendar. Parts and PPE stocked before the shortage.
Transfer notes, consignment notes, carrier licences, permits, EPR evidence, emissions. And every report anyone asks for: the council, the board, the auditor, the customer. Written from the data, before the deadline.
Collection, treatment, trading, recycling, energy, producer responsibility. Municipal and commercial. Hazardous and inert. We built the software that ran these operations in thirty countries before we built the AI that runs them better.
Twelve years of routes, tickets, lifts, loads, disputes and reports from thirty countries are what our LLM is trained on. It knows every chapter of the European Waste Catalogue and the streams outside it. Pick any.
A focused LLM trained on waste, on top of the best models in the world. They bring the reasoning. Ours brings the yard.
It starts by asking about everything. You loosen the reins where it earns them. Anything that touches money always waits for you, and no setting turns that off.
Every row is a real action it can take in your operation. The summary updates.
Six steps, and the sixth leads back to the first. We don't take feature requests and we don't sell licences. Every time your business changes, we start again: as partners, listening.
A project to get you there. A recurring fee that scales with how much work the AI does for you. You pay for work done, not for seats.
We don't talk about AI.
We implement it.
No. It handles the routine exceptions so your dispatchers, traders and back office handle the ones that need judgement. In most operations we've seen, most of the day is routine. The people stay. The firefighting goes.
No. Operations is where we start, because that is where the money is made and lost, and where trust is earned. From there it runs the company around the operation: invoicing from lift records, timesheets from in-cab data, purchase orders from stock levels, compliance from the paperwork it already handles. Same AI, same rule: it does the routine, it asks you about money.
Municipal and commercial collection, trading, MRFs, energy from waste, EPR schemes. Any stream, from mixed municipal to clinical to C&D. Twelve years across thirty countries is what the AI is built on.
Yes. It reads from what you have: ERP, telematics, weighbridge, customer systems, market feeds. Nothing is replaced on day one. It sits on top and does the work between them.
The best frontier models in the world, with twelve years of waste-operations knowledge, your data, and tools built for the specific work. Your data stays yours and is used to run your operation, not to build someone else's.
Weeks. We come to you, study the operation, build, and run the first exceptions under your approval. You usually start with one part of the operation and widen from there.
A project to get you there, then a recurring fee that scales with the work the AI does. You pay for work done, not for seats or modules.
Any country, any stream, any size. We'd like to come and see how it runs, and show you what the AI would do with it.
or write to umutcan@evreka.co
For twelve years we were a good vertical software company. We built for waste operators in more than thirty countries: collection, treatment, trading, recycling. We digitised routes, containers, fleets, contracts and reports, and we learned what the industry already knew. Waste is not a process. It is a stream of exceptions. A truck breaks down, a customer calls, a load arrives contaminated, a price moves. Every day, in every operation, people handle what the software cannot.
Software follows rules. Waste doesn’t. We knew the ceiling of what we were building.
Eighteen months ago we decided to change what kind of company we are. It did not start with a product. It started with awareness, then with targets, and those did less than we hoped. What changed everything was our CEO opening a terminal, building small things with AI, shipping them, and asking everyone else to ship too. Not a strategy. An example. The climate of the company changed in weeks.
The hardest part was not learning AI. It was unlearning waste. Twelve years of experience tells you what is possible, and in a moment like this, that is exactly what holds you back. We had to push against our own expertise to see what the new tools could do.
Then we changed how we work with customers. For years, a customer asked and we built. That is a software company with an agency attached, whatever the technology underneath. Instead we went to a customer, listened, studied their operation, and came back with a solution built entirely with AI. It worked. We did it again. And then we said: if we can do this, we can dream bigger.
Someone will build the AI-first version of every great company. The great companies themselves rarely can. We are small enough to rebuild Evreka as that company, and we are doing it. We are not finished, and we don’t pretend to be.
So here is what we say to the waste industry. You don’t have to become an AI company. We became one so you don’t have to. Evreka’s AI knows waste. It sees what is happening across your routes, customers, streams, drivers and margins, and tells you what to do. It handles the exceptions that used to need a dispatcher. It prices new business on real cost and real margin. And it reports, to you and to your customers, without anyone assembling a spreadsheet on a Friday afternoon.
We don’t talk about AI. We implement it.