Traba

A recent MIT study reviewed 300 enterprise AI deployments. 95% delivered no measurable return. The cause wasn't model quality. The study calls it a learning gap: the tools don't adapt to how the work actually runs. They fail at deployment. Most agentic solutions are a bigger onboarding project than they are a business asset. Another login, migration, or dashboard that needs to be maintained. A team that has to remember to go use the shiny new expensive tool you just paid for. Value gets reported as usage, because the numbers you actually care about never move. You were never meant to shape your work around an AI tool. Agentic AI was meant to be shaped around the work you already do. That's what we built Neo for. It goes inside the stack you already run, so your WMS, ERP, HRIS and payroll finally know what each other are doing. A dashboard hands you a number and stops. Neo keeps going: it catches the drift, makes the move, and shows its work. Nobody's job changes. The output does. The only things that move are margin and the stress levels of the people on your floor. If you're scoping AI for next year, ask any vendor one question. Does this live in the systems my team already opens every morning, or alongside them?

We've spent the last few quarters on site with our Neo design partners. Every first visit, we ask what their biggest constraint is. Everyone has an answer, and most of the time it's wrong. At one 3PL it was dock capacity, the expensive bottleneck the whole schedule is built around. We spent a day on the floor. Orders went out to the pickers in a few big waves a day, on a schedule nobody had touched in years. The floor would go quiet, the docks would sit empty, then everything landed at once right before the trucks pulled out. The docks weren't the problem, the timing was. The wave setup was in the WMS and the dock times were in the yard system, but nobody had put them next to each other. The fix wasn't to go and build out more docks, just to change when the work went out. Whatever yours is, it's probably not on anyone's list. Someone has been handling it for so long that it stopped looking like a problem. We'll do that first visit for anyone who wants one. No charge, and you don't have to be a customer. A day in your operation, and a straight account of what's worth automating. Find out what yours is. Link's in the comments 👇

Proud to be partnering with Fulfill.com 🤝

Last night we hand-selected builders to join us at Traba HQ for a recruiting event and the vibes were electric. What went down: ⚡ Jike Zhang and Moreno Antunes demoed DejaVu, our GenUI system — the agent designs and renders the exact interface an operator needs, live, on the fly. 🧠 Micah Blackburn unpacked The Dreaming — our agents run two brains, one learning in the moment and one consolidating overnight, so they never start from zero. 📈 Satvik Muddana broke down agentic evals and TraBENCH — sandboxed worlds, LLM judges graded against human graders, responsible hillclimbing, public benchmarks for agents that act on the physical economy. Shoutout to our partners at Paraform for helping pack the house with exactly the right builders. We're hiring top 1% talent across engineering, product, and data. Link in the comments!

Not sure what was better this morning - the views or the company! It was an honor hosting some of the sharpest minds in the industry at our Supply Chain Leaders Breakfast on the rooftop at Nine Orchard in New York City. A huge thanks to everyone who joined us for all the laughs and great conversation. And a special thank you to our co-host Kevin Lawton, CLTD from The New Warehouse. We hope to see you at the next one! Chad Carleton Maggie Barnett Lacie Griffin Hanako Tsuchiya Seth Rubin Scott Chamberlain Benn Mendelsohn Scott Hothem Tufan Aksahin Bill Gilooly Paulette Alviti Vanessa M. Vinicius V. Bryan Corbett Alexander K. Jessica Dzugan George Saikaly Michael Woolfson Qianqin L. Bryan Corbett Karina El Baze Anthony Gomez Mike Shebat Akshay Buddiga

Next Wednesday, August 26 @ 6-9pm, Traba and Paraform are hosting an intimate evening of engineering talks, food and discussion at the Traba NYC Flatiron office, covering one question: How do you build agents that survive the variance, scale and chaos of the $40 trillion global industrial supply chain? Signups are open to all, but we'll be hand selecting a group of ~30 engineers and PMs who have driven exceptional outcomes with agentic engineering. We're proud to host this event with Paraform, Traba's long time trusted hiring partner for top 1% talent acquisition. Register below 👇 👇 👇 https://luma.com/jxq65cgo

Condé Nast referred to the Amangiri resort as "what a luxury hotel on the moon would feel like." 🌙 I want to send you there for 5 nights (or just take the $10-20K in 💵 cold hard cash 💵). The quid pro quo: refer me a world class engineer in the next 30 days. Traba is building the AI operating layer for the $20 trillion global industrial supply chain, and I need the best engineers on the planet to build it. 👇Tag an engineer who wants to work on real-world problems that lift the quality of life for humans around the world. If we hire them, we'll send you $10-20K to book your dream Amangiri trip! 💅 🏝️

Everything you touched today arrived at your fingertips through the global supply chain: the coffee at your favorite neighborhood cafe, the iPhone in your hand, the cardboard box carrying your latest impulse purchase on your porch. None of it got there by magic. And many of the items nearly didn't arrive. They get to their destinations because somewhere in middle America, a warehouse supervisor is closing gaps by hand — a shift coming up a dozen people short, the count in the system not matching what's on the shelf, or a line stalling with a truck already idling at the door — before the day goes sideways. That scramble is the reality of the supply chain. The physical economy runs on it, and even though nearly everybody depends on it, most people rarely see it. Over the last thirty years, software drove the cost of information, communication, and now intelligence itself toward zero. That's why the digital world feels abundant. But the physical world never got that treatment. Things still cost too much and take too long to arrive, and the chain is coordinated by overloaded people operating based on their gut at the crack of dawn. The part of the economy everyone actually depends on is the part software never reached. We know, because we've spent the past five years inside it. What the physical economy needs is a brain above the operation. We’re building the layer that does the coordinating. We call it Neo. Read more on the vision for Neo below.

NFI operates the 5th largest warehouse footprint in the United States, running fulfillment and logistics at a scale most people never see. So hearing feedback like this from their team means a lot: "It's impressive to see the impact technology can have on contingent staffing. Traba has consistently delivered a level of speed, quality, and consistency that truly sets them apart. We're excited about what they've built and look forward to continuing to grow our partnership." Staffing is where we started, and being inside operations like this every day is what taught us how the physical supply chain actually works, where it breaks, and what the data really looks like underneath. That understanding is why we're building Neo, the AI layer for the operations that move the physical economy. Staffing proved we can bring real technology to an industry that's gone without it for too long and Neo is how we take that much further. There's a lot more coming.