Multi-expert AI/ML specification review with scoring gate — model architecture, evaluation rigor, safety/alignment, and production readiness for AI systems and LLM apps
Multi-expert architecture review — boundaries, integration patterns, failure modes, evolvability
Multi-expert business analysis with advisory recommendations (no scoring gate)
Multi-expert intelligence pipeline review — discovery quality, ingestion resilience, scoring validity, platform compliance, taxonomy coherence, cost efficiency
Multi-expert mobile/native app specification review with scoring gate — Android, iOS, Swift, SwiftUI
Multi-expert personal-development review with scoring gate — learnability, adoption, human-centeredness, and capability impact for talent/learning/AI-augmentation designs
Multi-expert research and discovery panel with source evaluation, API feasibility, collection strategy, and intelligence gap analysis. Use when evaluating data sources, APIs, scraping strategies, OSINT collection plans, or any research/discovery effort that needs expert validation before implementation.
Multi-expert security review — threat modeling, secrets handling, LLM/prompt injection, data classification, incident response