From dorm rooms to doorsteps, the Movana founder believes the future of moving begins long before the truck arrives—with better information about the physical lives we’re taking with us.
Moving has always required a peculiar kind of memory test.
Before the boxes are taped, before the truck pulls up, before anyone carries a sofa down three flights of stairs, someone has to explain what exactly is being moved. How many boxes? What kind of furniture? Is there an elevator? A long walk from the building to the truck? Something oversized, fragile or difficult to disassemble?
For decades, much of that information has been reconstructed through phone calls, walkthroughs, photographs, text messages and, sometimes, educated guesses.
Micah B. Lewis thinks that is where many moving problems actually begin.
Lewis is the founder of Movana Inc., an AI-powered moving platform designed around a deceptively simple idea: inventory first. Instead of beginning with a quote, Movana allows users to photograph their belongings with a smartphone and use artificial intelligence to transform those images into a structured visual inventory. Its conversational AI assistant, Ana, can then gather details that photographs alone cannot explain, including parking, elevators, access conditions, fragile belongings and other logistical requirements.
For Lewis, the idea did not emerge from looking for an industry in which to deploy artificial intelligence. It came from working inside the moving business.
After participating in more than 1,000 moves through Way You Move Movers, Lewis saw the same disconnect repeatedly: customers and movers were often making decisions from two different versions of the same move.
“I eventually realized that the fundamental problem was not simply transportation. The moving industry lacked a reliable, structured digital record of what was actually being moved.”
That realization became Movana. And Lewis believes its implications could stretch considerably further than getting furniture from one address to another.
We spoke with Lewis about information symmetry, responsible AI, privacy, the strange logistics of sending a child to college, and why the humble household inventory could eventually become digital infrastructure for the things we own.
You’ve said many of the moving industry’s problems begin before a truck ever arrives. What did you witness firsthand that made you realize the problem wasn’t simply transportation, but information?
The insight behind Movana came from years of working directly inside the moving industry and seeing the same problem repeat itself: the move often became difficult long before a truck arrived.
Through Way You Move Movers, I have been involved in more than 1,000 moves. Customers would describe what they owned over the phone, send a few photos or try to remember everything from memory. Movers would then estimate labor, truck size, equipment and time from that incomplete information.
Then moving day would arrive and reality might look very different. There could be twice as much furniture as expected, dozens of additional boxes, items requiring disassembly, oversized pieces, stairs, elevator restrictions or long carries that had never been discussed.
That disconnect creates problems throughout the moving ecosystem.
I eventually realized that the fundamental problem was not simply transportation. The moving industry lacked a reliable, structured digital record of what was actually being moved.
That became the foundation for Movana.
Movana begins with the inventory rather than the quote. Why does reversing that order matter?
Traditionally, moving begins with a quote. The customer calls a mover, tries to describe everything from memory, answers a series of questions and then asks the mover to estimate labor, truck capacity, timing and cost.
Movana reverses that process.
We believe the inventory should come first because the inventory is the source of truth for almost everything that follows.
Saying someone is moving a two-bedroom apartment tells a mover very little. There could be 20 boxes or 100. There might be a sectional sofa, oversized artwork, fragile electronics, exercise equipment or furniture requiring disassembly.
A visual inventory makes the conversation more precise.
With Movana, the customer can create a digital record of what is actually being moved before requesting services. That gives the customer and moving company a shared starting point.
That creates something the moving process has historically lacked: information symmetry.
AI is being added to almost everything right now. Where does it actually create value here—and where should human judgment still lead?
For Movana, AI is valuable because moving has traditionally required people to manually translate the physical world into information.
Movana uses AI to dramatically reduce that friction. A customer can use a smartphone to capture their belongings and turn what the camera sees into a structured visual inventory rather than manually typing every television, chair, dresser, box or piece of furniture into a spreadsheet.
But AI should not replace human judgment.
A photograph may identify an antique dresser, but an experienced mover understands what it means to carry that dresser down a narrow staircase. AI may recognize artwork, but a professional still needs to determine whether specialized handling is required.
Our philosophy is not to remove people from the process. It is to give them better information before they make decisions.
AI creates the information advantage. Human judgment determines what to do with it.
A visual inventory can potentially reveal where someone lives, what they own, how their home is organized and, in some cases, what their belongings may be worth.
What does trust mean when AI is identifying someone’s belongings and collecting information that could affect a moving estimate?
Trust is fundamental to moving because customers are sharing two deeply personal things: what they own and where they live.
If AI identifies a television, dresser, sofa or other belonging, the customer should be able to see that inventory, verify it and make corrections. If something is missing, it can be added. If something has been identified incorrectly, it can be changed.
We do not want AI creating a mysterious assessment that neither side understands. The objective is a shared visual record.
We believe AI should increase transparency, not reduce it.
Ultimately, we want AI inside Movana to function as an assistant rather than an invisible authority.
A visual inventory could become one of the most sensitive digital records someone has. How are you thinking about privacy?
Data stewardship cannot simply be treated as a compliance exercise. It has to be part of the product philosophy.
Movana is not just collecting product preferences or browsing behavior. We are potentially helping someone create a persistent digital record of their physical belongings.
The customer should remain at the center of the ecosystem.
The fact that a Movana inventory could potentially help with moving, storage, renters insurance, homeowners insurance, donation or resale does not mean every provider should automatically receive access to everything the customer owns. Those should be permission-based interactions.
There is also an important distinction between understanding an object and making assumptions about the person who owns it. Movana’s purpose is to help people organize, manage and act on their belongings—not to create unnecessary profiles about someone’s lifestyle simply because AI can see what is inside a room.
That boundary matters.
One of Movana’s early applications has emerged in a place where possessions, logistics and emotional transition collide: college.
At the University of Central Florida, Movana has been testing a model that asks families to begin thinking about spring move-out while they are still unpacking during fall move-in.
What has the UCF experience taught you about what moving means for students and parents?
One of the biggest things UCF taught us is that college moving is not a single event. It is a recurring lifecycle.
For many families, freshman move-in is one of the first major transitions between parent and student. Parents are trying to make sure their child has everything they need, while the student is beginning to manage a home and possessions independently.
Then spring arrives. Students may be dealing with finals, travel, housing deadlines and packing at the same time. Parents may be hundreds of miles away trying to coordinate logistics without even knowing exactly what is still inside the room.
That is why we believe the best time to begin planning move-out is actually during move-in.
Students want convenience and less work. Parents often want visibility, predictability and, perhaps most importantly, time back.
Longer term, a student may first create a Movana inventory in a dorm room at 18. That record can potentially follow them into an off-campus apartment, their first post-college relocation and eventually their first home.
College gives us an opportunity to establish the behavior early.
How do you make moving more predictable without simply shifting power from the moving company to the consumer?
The goal is not to give consumers leverage over movers or movers leverage over consumers. The goal is to give both sides a better source of truth before the transaction begins.
Importantly, the goal is not necessarily to make moving quotes cheaper. It is to make them more accurate and predictable.
An artificially low estimate can create just as many problems as an excessive one. If a job truly requires four movers and a larger truck, sending two people and inadequate equipment is bad for the customer, the crew and the moving company.
For us, fairness does not mean one side always gets the better deal. It means both sides enter the transaction with a clearer understanding of what has actually been agreed to.
When does a moving app become infrastructure?
A moving app becomes infrastructure when the information it creates remains useful after the move is over.
Once someone has a structured record of their belongings, they can begin answering a different set of questions.
What should I keep? What should I store? What should I sell? What should I donate? What needs insurance documentation? What needs to move to the next home?
Today, those decisions often take place across completely separate companies and systems, requiring the customer to recreate the same information repeatedly.
We believe the inventory can become the common information layer connecting them.
But earning the right to become that infrastructure requires more than technology.
We have to prove that the inventory is accurate and useful. We have to create meaningful value for the businesses receiving that information. And most importantly, we have to earn the customer’s trust and protect their control over the record.
If we accomplish those things, the inventory itself becomes the durable asset.
How has building an AI company changed the way you think about entrepreneurship?
Building an AI company has taught me that technology can tempt founders to begin with what is technically possible. My instinct is to begin with what is repeatedly painful.
We did not start by asking, “How can we add AI to moving?”
We started with a problem I had experienced hundreds of times: the customer and mover frequently do not have the same understanding of what is being moved.
AI became valuable because it offered a better way to solve that problem.
That is the difference between designing for someone and designing with someone.
Technology can make a solution scalable, but proximity to the problem is what makes the solution relevant.
Start with the work. Then determine where the technology can make the work dramatically better.
What part of today’s moving experience do you hope the next generation finds hard to believe ever existed?
Five years from now, I think moving should feel much less like starting from zero.
If Movana succeeds at the scale we imagine, customers will already have a living digital inventory of their belongings before they ever request a moving quote.
AI will make much of this possible, but ideally the customer will barely think about the AI itself.
They will simply notice that documenting a home takes minutes instead of hours, that their mover already understands what is coming, that estimates are easier to compare, that fewer surprises occur on moving day and that they do not have to explain the same belongings to five different companies.
That is what good technology eventually does. It disappears into the experience.
And if there is one part of today’s moving process that I hope the next generation finds hard to believe ever existed, it is this: people once called a moving company, verbally described everything they owned from memory, and then expected both sides to accurately predict the cost and complexity of the move from that conversation.
I think future customers will look at that the way we now look at printing driving directions before a road trip.
The information should already exist.
Moving is ostensibly about transportation, but it is also about transition. A dorm room becomes an apartment. An apartment becomes a first home. Furniture is accumulated, sold, inherited, stored and discarded. The objects change as our lives change.
Movana‘s wager is that the information surrounding those objects shouldn’t have to disappear every time the address does.
That makes its most interesting question less about whether artificial intelligence can recognize a sofa. It is whether people will eventually expect their physical possessions to have the same kind of persistent, portable information layer that already surrounds so much of their digital lives.
Before you move it, inventory it.
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