Sunday has raised $200 million in total funding, including a Series B round.

The company was founded in 2024 by Tony Zhao and Cheng Chi, both of whom came out of Stanford robotics research, and grew from two people in a single apartment at the end of 2024 to roughly 79 employees by mid-2026, with headquarters in Mountain View, CA.

Before the Series B, Sunday raised a seed round and Series A as it transitioned from academic research into a product company.

Sunday builds Memo, a wheeled home robot for household tasks such as clearing tables, loading dishwashers, picking up objects off the floor, and folding laundry.

Memo weighs roughly 170 pounds and uses a wheeled base with a telescoping vertical spine that can reach from floor level up to about seven feet. Instead of a five-fingered hand, it uses a simplified 3-finger gripper modeled on the three fingers humans most commonly use together for household grasping, such as opening a dishwasher door, picking up a cup, or grabbing a piece of clothing.

The wheeled base avoids the balance and stability problems common in bipedal humanoids, prevents falls, and keeps the mechanical system simple enough to target a sub-$10,000 price point at scale. Current prototypes range from $6,000 to $20,000 depending on cladding, with most of that variance expected to collapse once injection molding replaces the current CNC-and-hand-painting process.

Sunday trains Memo without deploying teleoperated robots into homes. Instead, it distributes Skill Capture Gloves, a $400 wearable that replicates the robot's 3-finger gripper and pairs with a wide-field-of-view camera hat, to workers who perform household chores in their own homes. Those demonstrations are converted into robot-usable training data through a software layer called Skill Transform, which achieves roughly 90% fidelity in translating human motion into robot-equivalent trajectories.

That process has produced a training dataset of approximately 10 million behavioral trajectories with zero actual robot involvement. The data feeds ACT-1, Sunday's foundation model, which combines map-conditioned navigation with long-horizon manipulation in a single system. In public demos, Memo has shown zero-shot generalization across six previously unseen Airbnb homes, completing full table-to-dishwasher sequences, handling wine glasses with force-controlled precision, and folding socks end-to-end without environment-specific training.

Memo's design is intentionally non-threatening, cartoon-like and topped with a baseball cap, to feel approachable rather than humanoid.

Sunday is a vertically integrated B2C hardware and software company selling directly to consumers, with a long-term model built around robot ownership or subscription paired with continuous software improvement.

Its monetization logic follows consumer electronics: a hardware sale or monthly lease captures upfront value, followed by software updates that improve performance over time and increase retention. At a target price below $10,000, Sunday frames Memo as a premium home appliance rather than a luxury item, comparable in price to a high-end refrigerator and potentially justifiable against the $10,000-$12,000 annual cost of a human housekeeper if performance reaches equivalence.

Sunday's cost structure rests on two design choices. The wheeled, 3-finger form factor avoids the actuators, balance systems, and precision components that raise the bill of materials for bipedal humanoids. The company also uses low-cost, mechanically imprecise actuators and relies on AI vision to correct inaccuracies in real time, reversing the traditional robotics model in which hardware precision was the primary cost driver.

Its glove-based data collection model changes training economics as well. By paying household workers up to $60 per hour to collect demonstrations rather than deploying fleets of teleoperated robots, Sunday avoids the capital intensity of maintaining and operating physical robot infrastructure during the pre-commercial phase. That lowers burn while generating a proprietary dataset that competitors cannot easily replicate.

The long-run margin profile depends on how quickly manufacturing costs compress with scale. Current prototype cost variability is driven largely by low-volume cladding processes; at injection-molding volumes, that variance should fall significantly. The company that reaches scale first in home robotics will likely have a meaningful cost advantage, which helps explain Sunday's push toward its late 2026 beta while the product remains imperfect.

Sunday competes in a market that has split into two camps: companies betting humanoid form factors are the right architecture for home robots, and companies betting simplified, cheaper non-humanoid designs will reach consumers faster and with higher reliability. Sunday is in the second camp, alongside The Bot Company, while 1X, Figure, and others are in the first.

1X is Sunday's closest philosophical rival among home-focused companies. Its NEO robot is a full-size, soft-bodied bipedal humanoid priced at $20,000 upfront or $499 per month, targeting the same household labor categories, tidying, dish adjacencies, laundry, and object pickup, with a different hardware bet.

1X's argument is that homes are built for human bodies, and that a robot optimized for doors, stairs, cabinets, and human tools should match that form. Its technical core is a world model called 1XWM that lets NEO simulate possible futures and learn from virtual failures before real-world execution. The open question is whether that architecture advantage compounds faster than Sunday's data-volume advantage from the glove program.

The Bot Company, founded by former Cruise CEO Kyle Vogt and valued at over $4 billion on $300 million raised, shares Sunday's anti-humanoid positioning and sub-$10,000 price ambition. Vogt's thesis is that home robots should start with forgiving, high-frequency tasks like toy pickup, where 90–95% reliability is sufficient, rather than tasks like laundry that require near-perfect execution.

The main difference from Sunday is data strategy: The Bot Company rejects teleoperation in homes on privacy grounds and bets on in-situ autonomy data, while Sunday's glove program generates training data before any robot enters a home. Weave Robotics takes the specialization logic further with Isaac 0, a stationary laundry-folding robot already shipping to Bay Area homes at $7,999, competing directly with Sunday on laundry while avoiding the mobility problem.

Figure AI, the most heavily funded company in the category at $2.5 billion raised and a $39 billion valuation, is the most commercially advanced competitor but is sequencing industrial deployments first. Its BMW partnership, Helix VLA stack, and Project Go-Big, which gave Figure access to 100,000 residential units through a Brookfield partnership to collect first-person home video, amount to a home-data strategy that could accelerate its consumer timeline.

Tesla's Optimus program is the largest long-run incumbent threat: if Tesla brings manufacturing scale and supply chain leverage to a home robot, it could compress prices faster than any startup. Chinese competitors including Galbot, Unitree, and Fourier add pressure, with structural supply chain advantages in motors, actuators, and batteries that give them a 40–60% cost reduction on standardized components relative to US-based manufacturers.

Sunday's initial market is households willing to pay a premium for automated chore assistance, but the underlying platform, a robot that can generalize across home environments from human demonstration data, has expansion vectors beyond the first product. The main vectors are a broader task library, eldercare use cases, and B2B2C distribution through property and hospitality.

Memo launches focused on a narrow set of high-frequency manipulation tasks: table clearing, dishwasher loading, object pickup, laundry adjacencies. Each new task category expands the addressable market by making the product useful to a broader set of households.

The glove program is the mechanism for that expansion. Because Sunday can deploy gloves to workers in new home environments and collect demonstrations for new tasks without deploying physical robots, it can add capabilities faster and at lower cost than competitors relying on teleoperated robot fleets. As the task library grows from tidying to cooking-adjacent tasks to eldercare assistance, the robot shifts from a convenience product toward a necessity product for a larger population.

The global aging population is a large market for home robots that extends beyond convenience. In Japan, China, and Europe, demographic pressure is increasing demand for in-home assistance that human labor cannot fill at scale.

Sunday's wheeled, stable form factor, which cannot fall and poses lower injury risk than a bipedal humanoid, is better suited to eldercare environments than full-size humanoids that weigh more and move less predictably. A robot that can reliably fetch objects, clear surfaces, and assist with light physical tasks in the home of an elderly person addresses a large need underserved by existing products. Fourier's GR-3 is the clearest competitor pursuing this angle, but Sunday's lower price target and non-threatening aesthetic create a different positioning in that segment.

Short-term rental properties, hotels, and managed residential buildings represent a B2B2C channel that could increase Sunday's deployment scale before the direct consumer market matures. Figure's Brookfield partnership, collecting home video from 100,000 residential units, shows that property managers are already engaging with home robotics companies as potential operators.

For Sunday, deploying Memo across a managed apartment portfolio or short-term rental network would generate both revenue and diverse real-world training data that compounds model quality over time. Each new home environment the robot operates in adds to the distribution of layouts, objects, and edge cases that make the underlying model more generalizable, creating a data flywheel that is difficult for later entrants to replicate.

Chinese cost advantage: Chinese robotics manufacturers including Unitree, Galbot, and AgiBot have structural supply chain advantages in brushless DC motors, actuators, and batteries that translate to 40–60% lower component costs, and unlike 1X, which has spent a decade developing proprietary motors, Sunday's wheeled platform relies on commodity actuators that are directly exposed to this cost pressure at scale.

Consumer trust and the service model: The hardest unsolved go-to-market problem in home robotics is not hardware or AI but the full service layer, installation, onboarding, failure recovery, maintenance, and privacy in a private home, and Sunday must deliver something close to an appliance-grade experience to consumers who have little tolerance for the kind of supervised pilots that enterprise buyers accept.

Data-to-product translation risk: Sunday's technical thesis rests on the Skill Transform layer converting glove demonstrations into robot-usable training data at roughly 90% fidelity, but that 10% gap, combined with the mechanical imprecision of low-cost actuators, means the robot's real-world performance in uncontrolled consumer homes may fall short of what controlled demos suggest, with no clear path to closing that gap without the expensive teleoperation pipeline Sunday has explicitly rejected.