Trash collection hasn't changed structurally since the 1960s. The truck still goes door to door, stop by stop. We're building the system that ends that model — starting where it breaks down first.
Every residential route sends one truck to 300–600 individual doors. The driver dismounts, lifts, empties, and repeats — for hours. Nothing about this sequence has been automated. It's pure labor, compounding in cost every year.
Routes get combined, pickups get missed, operators face contract penalties. The labor problem isn't improving — it's accelerating. Wages are up 34% since 2020 with no structural relief.
The billing unit is the ton. The cost unit is the stop. Operators absorb the gap on every route, every day. Across millions of routes annually, that's tens of billions in structural inefficiency with no fix in the current model.
The real problem is that the truck goes to the waste. The waste should come to a container. Robotrash changes the collection architecture, not just the labor input.
Trash systems don't talk to each other. Fill levels aren't tracked. Routes run on fixed schedules regardless of demand. A residential route is 300–600 stops of the same mechanical sequence, every single day.
The truck goes to the waste. The waste should come to a container.
Replacing the driver doesn't fix this. The collection architecture is fundamentally wrong.
We're not trying to replace every trash truck. We're starting where the model breaks down hardest: dense controlled environments where routes are predictable, traffic is limited, and one operator manages hundreds of units.
One rover. One zone station. One contract. Deployable now.
Apartment complexes, gated communities, and private campuses are the first market — before we've touched a single public street.
The first version does not require perfect city-wide autonomy. Fixed routes, remote assist, bagged trash only, controlled environments. The navigation stack is well-understood.
Start constrained. Prove the model. Expand the environment.
The active engineering challenge is the waste acceptance mechanism: the specific problem no delivery robot addresses today.
This window didn't exist three years ago. The company that builds the first deployable version now controls the physical infrastructure, and that infrastructure isn't software-switchable.
LiDAR dropped from $75,000 to under $500. Electric drivetrains are now cost-competitive at sub-1-ton scale. The hardware to build a deployable rover finally costs less than a used car. That wasn't true in 2021.
Sanitation wages are up 34% since 2020 (BLS). Driver retention is at historic lows. Every year the status quo holds, the economic case for automation strengthens — and the urgency for operators grows.
The EPA's Clean Trucks Plan (Phase 3) sets strict zero-emission targets for vocational fleets through 2032. State mandates require 75% of new garbage trucks to be zero-emission by 2035. Fleet operators are already budgeting for this transition.
Infrastructure that scales to millions without breaking is a software problem. Waste collection hasn't been treated as one yet.

Spent over a decade building large-scale infrastructure at Twitter/X, Affirm, and IBM Watson — systems designed to handle millions of events with minimal human intervention. That's the same problem class as waste collection, different physical layer.
The gap between how trash collection works today and how it should work is too specific and too large to leave alone. The first version doesn't need to be perfect. It needs to be deployable.
We're mapping our first deployment partners and talking to investors who understand physical infrastructure built software-first. If that's you, let's talk.