Anti-Scam Root Cause Analysis Crew with CrewAI & Together AI
Preventing public scams requires fast cross-analysis of reported phishing signals and telecom patterns. Deploy a collaborative agent crew using CrewAI and Together AI inference to automatically ingest scam alerts, identify root causes, and produce public threat advisories.
What you are building
The core problem, expected build, and operating context for this challenge.
Orchestrate an anti-scam intelligence agent crew using CrewAI and high-throughput Together AI models.
How work is evaluated
Evaluates threat categorization speed, root cause accuracy, and structured alert output.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
correct_category
Checks category accuracy
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
root_cause_accuracy
Precision of root cause vector detection • target: 0.95 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Configure CrewAI roles, tasks, and agents for threat intelligence
Integrate Together AI inference endpoints for open-weight model acceleration
Generate actionable public sector scam mitigation advisories
Reference links and supporting material
Synthetic dataset of SMS, email, and social messaging scam reports.
How this agent runs
Evaluates threat categorization speed, root cause accuracy, and structured alert output.
Challenge input
JSON containing reported SMS body and URL
CrewAI
Multi-agent crew orchestration
Together AI
Fast open-weights model execution
Evaluated output
JSON containing category, primary_vector, target_institution, recommended_action
- Checks category accuracy
- Precision of root cause vector detection • target: 0.95 • range: 0-1
- Benchmark: ScamThreat-Bench
- Root Cause Accuracy target: 0.95
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
View technical recipe
Configured tools
- CrewAI · Required
- RAI · Optional
- Together AI · Optional
- Together AI · Optional
Evaluation contract
- correct_category · Weight 1
- root_cause_accuracy · Weight 1
Recipe state
This is a preview. The configuration can change before the evaluation recipe is locked.