Runwise•AI Agent Reliability Infrastructure

Build agents you can actually trust.

Production agent reliability with deterministic evaluations, sub-millisecond model routing, and instant rollback.

Step 1RequestNormalized query
Step 2Route< 0.1ms CPU
Step 3ExecuteSandboxed tools
Step 4EvaluateDeterministic
Deterministic Evals
50
Evaluation Tasks

35 Dev + 15 Frozen Holdout tasks across 4 customer service domains.

Automated Suite
151 / 151
Passing Tests

Platform and API integration test suite across 28 modules with 0 regressions.

Trace Replay
-57.5%
Modeled Cost Reduction

$3.54 vs. $8.33 / 1k requests under empirical trace replay versus Always Pro.

Cost reduction is estimated via empirical trace replay over baseline trajectories, not production A/B traffic. Test count reflects unit and integration suite health across 28 modules.

System Architecture

Three Reliability Pillars

Engineered for low-latency routing, deterministic evaluations, and zero-downtime recovery.

Dynamic Model Tiering

Scores lexical risk in < 0.1ms on CPU, dispatching routine queries to Flash and reserving Pro for complex edge cases.

Input
User Request
Sanitized Prompt
Classifier
AutoRouter
Score: 0.12 (< 0.45)
Target Model
Gemini 2.5 Flash
$0.075 / 1M tokens
Execution
SandboxDB
< 2ms SQLite
Empirical Benchmark

Cost & Latency Optimization

Runwise dynamically routes routine customer requests to Gemini Flash while reserving Pro for high-liability edge cases.

Always Strong (Gemini 2.5 Pro)Baseline
$8.33/ 1,000 requests
Relative Cost Index100%
Median Latency (p50):10.33s
Adaptive Semantic Router (Runwise)Active
$3.54/ 1,000 requests-57.5%
Relative Cost Index42.5% (-57.5% Cost)
Median Latency (p50):3.82s (2.7x faster)

Cost and latency figures are empirical trace-replay estimates evaluated across 35 benchmark dev tasks under identical task accuracy constraints.

View full methodology
Engineering Connect

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