KAAL — Knowledge Agent Arbitration Layer

KAAL (Knowledge Agent Arbitration Layer) is a full-stack adversarial foresight engine built entirely on AMD Instinct MI300X using ROCm 7.0. Most AI gives you confident-sounding guesses. KAAL gives you arbitrated intelligence — four autonomous agents that debate, attack, reconcile, and deliver calibrated long-horizon forecasts. No slop. No repetition. Always ends at a complete sentence. THE AMD STACK: We ran the complete pipeline on a single MI300X — data collection from 208 scientific sources (IPCC, IEA, WHO, WEF, World Bank 2024-2026), synthetic data generation via Qwen-72B on AMD, LoRA fine-tuning of Qwen2.5-7B in full bfloat16 precision, and GGUF Q4 quantization via llama.cpp — all on the same AMD server. Fine-tune completed in under 3 hours. Training loss: 2.5 → 0.47 (81% reduction). THE AGENT ARCHITECTURE: Architect builds the thesis. Contrarian attacks every assumption. Analyst reconciles the conflict. Synthesizer delivers a PhD-level calibrated forecast with confidence levels that decrease as the time horizon increases. DEPLOYMENT: Quantized to GGUF Q4_K_M (15GB → 4.4GB) and deployed permanently free on HuggingFace Spaces via llama-cpp-python. No GPU needed post-training. Zero ongoing cost. BUSINESS VALUE: $4.5B strategic foresight market. Replaces $50,000/month analyst panels at $1.99/hr on AMD. Buyers: infrastructure firms, sovereign wealth funds, HR strategy teams, defense contractors.