Build a Google ADK Brand Protection Agent with Lovable Web Prototyping
Rapidly growing D2C brands face trademark disputes and unauthorized product listings on e-commerce platforms. Create a Google ADK agent using Gemini multimodal models to identify counterfeit brand assets and output a functional Lovable UI dashboard to resolve trademark conflicts across retail channels.
What you are building
Develop a Google ADK visual inspection agent that flags illegal trademark usage and generates structured conflict reports integrated with Lovable prototypes.
How work is evaluated
Evaluates visual and text trademark collision identification precision.
Datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
detection_match
Confirms infringement detection trigger
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
confidence_score
Model confidence on trademark collision • target: 0.94 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Learning goals
Deploy Google ADK multi-modal agents with Gemini models for visual brand match analysis
Implement fuzzy string and trademark vector search logic for brand name detection
Integrate with Lovable tool interfaces to expose UI dashboards for trademark enforcement
Generate automated legal cease-and-desist draft reports
Resources
E-commerce product catalog listings with synthetic brand copy and trademark registry entries.
Challenge setup
Evaluates visual and text trademark collision identification precision.
Challenge input
JSON listing object with brand text and image reference
Google ADK
Multimodal agent development using Gemini
Lovable
Generates dashboard interface prototypes
Evaluated output
JSON triage outcome with collision confidence and summary
- Confirms infringement detection trigger
- Model confidence on trademark collision • target: 0.94 • range: 0-1
- Benchmark: IP Dispute Detection Benchmark
- Confidence Score target: 0.94
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
Shows the first task, up to three tools, and up to three evidence items.
View technical recipe
Configured tools
- Google ADK · Required
- Lovable · Optional
- Google · Optional
Evaluation contract
- detection_match · Weight 1
- confidence_score · Weight 1
Metrics
- confidence_score · Target 0.94
Benchmarks
- IP Dispute Detection Benchmark
- security
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON listing object with brand text and image reference
Output: JSON triage outcome with collision confidence and summary
Execution harness: Python
Evaluation tools
- Google ADK · Agent Framework
- Lovable · UI Engineering Tool
Recipe freeze marker
No recipe freeze time is recorded.