36Kr Exclusive | Pet health model company secures two consecutive rounds of funding, integrates hardware and software, and has served over 200 pet hospitals.

1. Addressing a Core Challenge in Pet Healthcare

The article highlights a fundamental problem: pet diagnosis is inherently difficult. Unlike human medicine, pets cannot verbally describe symptoms, and the field often lacks the structured, evidence-based data that powers human medical AI. Qialgorithm's approach directly tackles this by building a vertical, domain-specific AI model. Instead of relying on general-purpose AI, its system is trained on millions of specialized data points—medical records, images, and behavioral data. This allows the model to grasp nuances like breed-specific physiological differences and complex symptom patterns, moving beyond simple Q&A to provide diagnostic reasoning, risk alerts, and decision pathways. This represents a shift from generic AI assistance to a tool that understands the specific logic of veterinary medicine.

2. The "Software-Hardware" Flywheel and Closed-Loop Ecosystem

Qialgorithm's most significant strategic insight is its integrated ecosystem, which creates a powerful data flywheel and multiple value capture points.

• The Hardware Entry Point: Products like the ultra-light AI smart collar (19g) serve as persistent data collection devices in the pet's home environment. They gather continuous behavioral data (movement, sleep, posture), which is crucial for early anomaly detection and fills the gap between clinic visits. This is not just a gadget but a data acquisition layer for the AI.
• The Software & Service Core: The AI-assisted diagnosis platform, offered free to veterinarians, is the heart of the system. It boosts clinic efficiency and becomes embedded in the professional workflow. More importantly, every interaction generates data that refines the core model, creating a self-reinforcing cycle: more users → more data → better AI → more users.
• Monetization & Full-Cycle Service: With an internet hospital license, the platform can complete the service loop. After AI-assisted consultation, it can recommend medications, facilitate referrals to partner clinics, and offer follow-up care. This moves the business from a pure software tool to an integrated health service platform, capturing value across diagnosis, treatment, and ongoing care.

3. Technical Differentiation and Strategic Barriers

Founder Chen Li emphasizes that their advantage isn't a single feature but a deeply integrated, self-developed tech stack. While they don't make their own chips, they control the algorithms, the edge-computing framework, and the hardware design. This "full-stack" capability allows for optimization that is difficult for competitors replicating off-the-shelf solutions to match.

Furthermore, they've solved the personalization problem through a two-pronged approach:

1. General Model Scaling: The core model's accuracy improves with a growing user base and more diverse data.
2. On-Demand Personalization: Users can upload a short video to quickly generate a custom model for their specific pet, addressing unique behaviors in minutes. This combines broad generalization with hyper-personalization.

4. Vision: From Product to Infrastructure Platform

The company's ambition, as stated in the interview, is to become the "foundational platform for pet health management." The immediate plan to build a vertical search and recommendation engine for the pet industry signals a move to control the information and service discovery gateway for pet owners. By integrating data from wearables, clinical interactions, and user behavior, they aim to position themselves not just as a tool provider, but as the essential infrastructure upon which pet health services are built. This turns their early technical and data moat into a potential ecosystem moat, where the platform's value increases as more hospitals, service providers, and users join the network.

In conclusion, Qialgorithm's story is a compelling case of applying sophisticated AI to a specific, high-value vertical domain. By combining cutting-edge multimodal AI with a pragmatic, ecosystem-driven hardware-software strategy, they are building a defensible business that solves real clinical problems while establishing a data-rich platform for the future of pet care.