About the firm
We came from the warehouse, then built the technology.
Most robotics companies are technology teams looking for an industry. Rivendell Engineering is the inverse. We understood the problem and the customer before we understood the hardware, and applied engineering to a requirement we already knew first-hand.
Sixteen years on the operations side of the problem.
Rivendell Engineering is led by Craig Olivo, who has spent sixteen years in warehouse software and delivered Manhattan Associates WMS implementations for more than fifteen distribution operators, most of them running multiple facilities. That is a long time spent standing on distribution center floors watching inventory control consume labor that the operation needed elsewhere.
DC HAiVE exists because of that vantage point, not despite it. The product decisions that matter — a ground vehicle instead of an aerial one, escalation by exception instead of by volume, no infrastructure changes to the building — are operational judgments before they are engineering ones.
What we will tell you
If the honest answer is that your problem is a process problem, or that a system you already own does the job once it is configured properly, that is the answer you will get. We would rather lose a scope than sell one that does not move a number.
Advanced technology should not require a giant's budget.
As coding becomes increasingly commoditized, the value of engineering shifts from manual repetition to strategic creativity. We work in that paradigm — leaning on modern tooling to compress the repetitive part of both disciplines, code and fabrication alike, and spending the time saved on conceptualizing the right solution and getting it into service.
The result is working hardware and production-ready software without the bloat of a traditional development cycle. Whether you need a prototype part on a machine next week, a robot designed from the ground up, or the full DC HAiVE platform, supply chains of any size get access to engineering that until recently only the largest operators could afford to commission.
Built here
Chassis to inference, by the person who understood the problem.
The rover was designed and assembled in-house — the enclosure and mast, the camera array and its mounts, the navigation stack, the detection networks running on it, and the platform it reports to.
That is unusual, and it is the point. Every decision in the machine traces back to someone who had already spent years watching inventory control work on a real floor.
Disciplines
What the firm covers in-house.
DC HAiVE spans applied AI, robotics, mechanical design, cloud infrastructure and enterprise integration. All of it is built and maintained here.
Custom detection and recognition networks
Object detection networks trained on independently annotated warehouse imagery, tuned per facility, and deployed to run inference on edge hardware rather than in a datacenter.
Vision-based autonomous navigation and localization
Navigation and localization for aisle environments using camera vision alone, camera and sensor integration, and the safety behavior that lets a vehicle share a floor with people and forklifts.
CAD design, custom components and assembly
Mast and mount design, 3D-printed custom components, and full robot assembly — which is why the hardware is modular and serviceable at floor level instead of sealed and vendor-locked.
Multi-tenant platform, data model and WMS integration
The web platform, its schema and data model, the message infrastructure between rover and cloud, and the integrations that put results into a customer's system of record.
Azure infrastructure, CI/CD and containerized deployment
The infrastructure the platform runs on, the pipelines that ship it, and the containerized deployment model that keeps a multi-tenant system maintainable.
Next step
Start with a conversation, not a scope.
Tell us about the operation and where the hours are going. We will come back with a straight read on what would actually help — including if the answer is that you do not need us.