ARDR (Adaptive Recurrent Dendritic Reasoning) is a multi-stage AI reasoning architecture that orchestrates multiple specialized models working in parallel. Instead of relying on a single model, ARDR coordinates experts in logic, pattern recognition, code, world knowledge, and adversarial thinking—all sharing a scratchpad and building on each other's insights to produce deeply verified responses.
The system works through six stages. First, a Task Profiler analyzes complexity and allocates resources. Then Structured Decomposition breaks the problem into symbolic, invariant, and formal views. Dendritic Branches run in parallel, each attacking the problem from a different angle. A Verification Layer actively tries to break its own hypotheses by generating counterexamples and measuring uncertainty. If confidence is too low, Adaptive Recurrence re-runs weak branches with targeted instructions. Finally, a Grand Synthesizer compiles all verified evidence into a coherent response.
ARDR offers three tiers: Low (Llama 3.3 70B, free), High (Deepseek V3.2), and Max (Claude Opus 4). It automatically detects conversational queries and skips heavy reasoning to save time and tokens. The result is an AI system that thinks deeper, catches its own mistakes, and produces multi-proofed answers for complex tasks.