12 Adaptive Pipelines

Kedge Adaptive Inference Pipelines dynamically reconfigure computation graph based on query complexity, available compute, and safety requirements while maintaining 27ms p99 guarantee.

Pipeline controller monitors 18 runtime signals: token rate, context density, reasoning depth, memory pressure, safety risk score, hardware utilization, stream concurrency, and temporal patterns.

Dynamic reconfiguration executes in 4.8ms: layer pruning, stream fusion, attention sparsification, precision reduction. Complex queries activate full 7-layer stack; routine queries use 2-layer fast path.

Compute budgeting: Inference budget allocated in 2ms quanta across stream lifetime. Budget violations trigger graceful degradation preserving safety constraints.

Agent routing: Query vectors projected against 3D agent manifold (kedge/keela/kite). Routing confidence threshold 0.78 prevents misrouting while maintaining 97% efficiency.

Safety integration: Pipeline Risk Scoring recalculates every 64 tokens. Risk elevation triggers conservative routing and enhanced validation without latency penalty.

Adaptive pipelines achieve 3.8x compute efficiency over static inference while preserving reasoning quality across workload variance.

Pipeline Controller: 18 runtime signals
4.8ms reconfiguration | 3.8x efficiency
Dynamic reconfiguration:
Layer pruning
Stream fusion
Attention sparsification
Agent routing:
3D manifold projection
0.78 confidence threshold
97% efficiency
Adaptive Intelligence
Reasoning complexity matched to compute budget. Quality preserved across workload variance.