Big 4 firms are strong at enterprise transformation strategy. DehazeLabs builds the actual systems. Here's an honest comparison of when each model makes sense — and where the differences matter most for AI in the physical economy.
Enterprise transformation strategy, multi-stakeholder alignment, change management, regulatory and compliance navigation, and the organizational capabilities needed to drive AI adoption across a large enterprise. If your primary challenge is getting organizational buy-in for an AI program or navigating a complex procurement process, Big 4 firms have deep experience.
We build production systems. Telemetry pipelines that process millions of events per second. CV inference platforms that run at smart-city scale. Agentic operations layers that execute real remediation. The gap between a consulting deck recommending "agentic operations" and an agentic operations system that works safely in production is an engineering gap — that's where we operate.
| Factor | Big 4 AI Practice | DehazeLabs |
|---|---|---|
| Primary output | Strategy decks, roadmaps, assessments | Production systems, deployed and operating |
| Team model | Senior partners + junior analyst pyramid | Embedded engineers, US lead + SA bench |
| Billing model | $300–600/hr, time-and-materials | Milestone-based, $300K–$4M engagements |
| Production infra AI depth | Varies by practice; often advisory-heavy | Core competency — T-Mobile, Hayden AI, EdgeTelemetry |
| Time to production | Often 12–24 months for complex programs | First production capability in 8–12 weeks |
| Post-launch operation | Typically hands-off after delivery | Ongoing platform operation available |
We'll tell you honestly in the first conversation whether we're the right team for your problem — and what we'd need to deliver if we are. No pitch deck required.