36Kr Exklusiv | Sequoia China und Monolith leiten die Beteiligung an der AI-Gesundheitshardwarefirma „Odyss“ an, der Betrag beträgt fast 200 Millionen Yuan.

Autor  | Zhang Ziyi

Redakteur  | Yuan Silai

Hard Kr has learned that the AI health hardware company "OdyssLife" (hereinafter referred to as "Odyss") has recently completed multiple rounds of financing in succession, with a total amount of nearly 200 million RMB. This round of financing was led by Sequoia China and Monolith respectively, and old shareholders Linear Capital and Creekstone continued to increase their investments.

The funds from this round of financing will be mainly used for the R & D of product software and hardware, global marketing, and team expansion.

At a time when the AI hardware track is highly sought after by capital, Odyss has entered a high - frequency scenario that has not been fully digitized - dietary health monitoring.

Odyss's first product, the Odyss N1, is the world's first Always - On smart necklace, which integrates multi - modal sensing capabilities such as image, audio, and motion, and can perceive and record users' dietary and exercise behaviors around the clock.

Pan Yuyang, the founder and CEO of Odyss, believes that in the daily high - frequency scenario of diet, existing smart wearable devices have physical limitations. Smart bracelets and rings have no visual perception and cannot sense food; while CGM belongs to medical devices and has a too strong medical attribute, which is naturally far from ordinary consumers.

In comparison, the advantage of the necklace lies in its light weight. A weight of just a few dozen grams is enough to achieve all - day "senseless wearing", and it has a natural wide - angle "God's perspective". It can be equipped with a low - power visual perception camera module to solve the pain point that traditional wearable devices cannot accurately capture "dietary data".

Specifically, the Odyss N1 has built a three - modal sensing system that "takes vision as the mainstay and audio and motion sensing as supplements". The core visual module abandons high - energy - consuming continuous video shooting and instead uses low - power "frame - shooting" technology to accurately capture data in all scenarios from dining in restaurants to home cooking, and can identify fine - grained information such as food types, volumes, and cooking methods.

At the same time, the audio and motion modalities are responsible for capturing semantic keywords of ordering and monitoring the user's metabolic state respectively, which helps to improve data accuracy. Based on this, the system will conduct in - depth learning on complex data such as calories, nutrients, and glycemic index, and finally generate personalized health intervention strategies for users based on their real - life states.

While many AI hardware start - up companies reuse mature supply - chain solutions to reduce costs, Odyss, which has obtained sufficient "ammunition", chooses to continuously optimize its products by customizing components.

At the hardware level, in order to achieve low - power, high - precision visual perception within the extremely small volume of the necklace, the company has customized a dedicated visual module and power supply system, and uses the more expensive titanium alloy CNC machining process to further enhance the appearance texture.

At the software level, Pan Yuyang believes that the accuracy of general models in vertical tasks such as identifying food types and estimating calories has not reached the commercial standard.

Therefore, Odyss has built a proprietary link of "pre - training of small models + post - training of large models". The large model is responsible for identifying food types and cooking methods, which is a crucial "backup" guarantee for dietary monitoring, and can retrieve the composition data of food from the database for calculation; the traditional computer vision (CV) algorithm has high accuracy and is specifically responsible for measuring food sizes and scanning codes.

Hard Kr has learned that after calculations by the Odyss team, the Odyss N1 can achieve an accuracy rate of over 90% in identifying the dietary calories of regular Western cuisine.

In terms of business model, Odyss plans to adopt a combination of "hardware + subscription". In the early stage, the company plans to maintain a high - end positioning of "tech trendy products" on the hardware side; but reduce the initial software subscription fees, aiming to quickly expand the user base and establish category awareness by lowering the usage threshold.

In terms of target customer groups, Odyss plans to initially target high - net - worth groups such as "bio - hackers", technology and finance practitioners, and fitness enthusiasts as its core users.

Pan Yuyang believes that these seed users not only have high data sensitivity and payment ability, but more importantly, they are also the definers of "social currency".

"In the consumption logic of high - net - worth individuals, wearable devices often serve as identity tags, and no one wants to wear an imitator that is 'the second in the market' on their chest," Pan Yuyang said.

Odyss has formulated a high - frequency SKU iteration route in its product planning. The company plans to launch a new series every 3 - 4 months. Through high - specification CMF (color, material, process) design - covering a variety of materials, it aims to meet the core users' needs for texture and personalization. In the future, the company will also launch SKUs that meet the aesthetic preferences of female users and gradually expand to a wider general public.

In terms of business progress, Odyss plans to start KOL testing in North America in April this year, launch on the crowdfunding platform in June, and is expected to officially ship through its independent website from August to September. In addition, Odyss will accelerate its global layout, aiming to expand its business to the Chinese mainland, Japan, and European markets within two years and establish a complete channel and data link in China.

Facing market competition, Pan Yuyang believes that future AI hardware will not be an all - in - one like mobile phones, but will have different functions.

The necklace is the best form for capturing dietary data. Although there are currently no direct competitors, it is in the stage from 0 to 1. If there are 3 - 5 direct competitors, they can also jointly reduce supply - chain costs and educate the market.

In terms of the team, Pan Yuyang has worked on the Xiaoyi algorithm and HarmonyOS products at Huawei, and has also worked on the Coze smart glasses at ByteDance. The core team members mainly come from leading domestic and international Internet, hardware, and AI model companies. Currently, the team is in the expansion phase and is focusing on recruiting talents for key positions such as front - end and back - end, algorithms, hardware R & D, and global marketing.