$SERV just introduced BRAID, a machine-native reasoning engine for LLMs & agents. ▫️ The problem: LLMs struggle with vague English prompts → errors & hallucinations. ▫️ The solution: BRAID converts prompts into structured, code-like reasoning diagrams that models follow much more reliably. Impact: Smaller, cheaper models can outperform advanced ones at 25–40x lower cost. Opens the door to scalable enterprise adoption. Removes reliability bottlenecks holding back on-chain agents & DeFAI. Adoption: Already piloted by the world’s largest white goods producer in call centers, with real-world financial decisions powered by BRAID. A Nasdaq-listed company is also exploring a revamp of their AI infra around it. Strategy: Open-source the research → credibility + mainstream adoption. Leverage BRAID across SERV’s agent stack → best-in-class reliability. Monetize via BRAID-native models & enterprise products. At ~$40M mcap, this is an early-stage AI infra play with enterprise traction, a clear technical moat, and direct relevance to DeFAI scalability. https://t.co/o5bFJlKgag