PAL.

The problem

Pet parents face their most stressful moments alone and off-hours. A late-night symptom check, a rushed vet visit, conflicting product advice, confusing insurance options, and slow-building chronic changes all pile up with no personalized, trusted place to turn. Generic online advice and general-purpose chatbots either over-alarm or under-escalate, and a single unsafe triage experience can permanently erode trust.

The pain is sharpest for anxious first-time owners and multi-pet households, who need reassurance and clear next steps but instead get fragmented tools that don't know their pet's breed, allergies, medications, or history.

The solution

PawPal is a safety-first, multi-agent pet care assistant that unifies symptom triage, breed-specific risk checks, product recommendations, insurance comparison, voice journaling, and vet-visit preparation in one place.

At its core is Nurse Nina, a triage system that never diagnoses or prescribes and always returns structured, explainable guidance across three tiers: Monitor at Home, See Vet Soon, or Emergency. Deep per-pet personalization draws on breed, age, allergies, medications, seasonality, and budget, with support for multiple species, six languages, and multiple tone modes. The same codebase powers both a consumer app and retailer-embeddable B2B distribution.

How it works

A deterministic orchestrator routes each request to specialist agents, with emergency detection and red-flag scanning running before the LLM ever executes, so critical cases are handled outside model variability. Triage then classifies urgency, surfaces nearby vets, and returns structured cards with disclaimers.

PawPal uses a multi-model strategy: GPT-4o as the primary for triage, chat orchestration, vet briefs, and vision, with Claude Sonnet 4.6 as a resilience fallback. Breed intelligence runs on a deterministic registry of 160+ profiles with rule-based alerts rather than embeddings, while RAG is bounded to clinical explanation only. Quality is gated by a 233-case eval suite (220 functional, 13 operational) with a required 100% pass rate before release, plus 30-second timeouts and rule-based fallbacks.

Who it's for

The end users are pet parents, with the highest-value segments being anxious first-time owners (ages 25–35) and multi-pet households (ages 35–55), followed by senior-pet caregivers managing chronic conditions and underserved exotic-pet owners.

The buyers are twofold. Through a B2B2C model, pet retailers and insurance carriers (with decision-makers like VP Digital and Head of Retention) license a white-label assistant to lift engagement and conversion. Pet parents are also direct buyers via the PawPal+ subscription for multi-pet management and deeper insights.

Why it matters

PawPal operates across pet care, insurance, AI, and digital commerce — markets growing at an estimated 15–20% CAGR through 2030. U.S. pet e-commerce exceeds $30B, pet insurance is growing ~20%+ annually yet remains underpenetrated at ~3–4%, and veterinary workforce shortages are accelerating demand for AI-assisted triage.

Currently late-prototype and pre-MVP, PawPal prioritizes distribution partnerships and an evaluation-first approach over direct acquisition. By separating probabilistic language tasks from safety-critical deterministic layers, it aims to be a trustworthy, auditable, partner-ready platform rather than a generic chatbot.

At a glance

Project

PAL

Built by

Manasa Shivarudra

One-liner

PAL is a multi-agent pet care assistant that unifies symptom triage, breed-specific risk checks, product recommendations, insurance comparisons, voice journaling, and vet visit preparation.