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Agent Reliability Testing
Ensure your production AI agents are resilient, predictable, and production-ready.
The Reliability Problem in Production AI Agents
Production AI agents are brittle. An agent that works perfectly in a controlled test environment can fail catastrophically in production. The reasons are predictable: token limit edge cases, tool failures, novel input distributions, inconsistent retry behavior, hallucinated function calls, and subtle prompt-model mismatches that only emerge at scale.
Traditional software testing focuses on deterministic execution paths. Agents are fundamentally probabilistic. The same input can produce different outputs on consecutive runs. This non-determinism makes reliability assessment difficult: you need to run your agent hundreds or thousands of times to understand its actual behavior, not just test it once and assume it works.
Worse, agent degradation is often invisible until it's costly. A deployed agent that succeeded 95% of the time last week might only succeed 70% of the time this week—perhaps due to a model update, a change in tool response format, or seasonal variation in input characteristics. Without continuous monitoring, these issues go undetected until customers complain or your SLA metrics tank.
badgeIA solves reliability assessment through comprehensive testing. We execute your agent thousands of times against realistic test cases, measure consistency, detect edge case failures, and alert you to performance degradation automatically. The result: you know your agent's actual reliability before it hits production.
How badgeIA Measures Reliability
Retry Patterns & Resilience
Agents often encounter transient failures: API timeouts, rate limits, parsing errors, or malformed tool responses. Reliable agents recover gracefully through retry logic. badgeIA measures:
- • How many retries does your agent attempt before giving up?
- • Does the retry behavior use exponential backoff or fixed intervals?
- • What is the eventual success rate after retry exhaustion?
- • How much extra latency do retries add in the P95 and P99 cases?
This reveals whether your agent can survive real-world friction or fails immediately on the first obstacle.
Consistency Scoring
Running the same input through your agent multiple times reveals outcome variance. A consistency score measures how often the agent produces the same (correct) result for identical inputs:
- • 100% consistency = agent always succeeds or always fails on repeated runs
- • 50% consistency = agent succeeds half the time, fails half the time (unreliable)
- • Low consistency indicates sensitivity to randomness, token ordering, or temperature effects
Low consistency agents are unsuitable for production. High consistency agents are trustworthy.
Latency Tail Analysis
An agent with 500ms P50 latency but 45-second P99 latency is unreliable for real-time systems. badgeIA tracks latency percentiles (P50, P95, P99) and computes outlier frequency to identify cases where agents get "stuck" or retry extensively. Understand the true worst-case performance of your agent, not just the average.
Tool Call Correctness
A common agent failure mode: selecting the wrong tool or calling tools with malformed arguments. badgeIA validates every tool call by checking:
- • Is the selected tool appropriate for the current task state?
- • Are all required arguments provided?
- • Do argument values conform to the tool's schema?
- • Are there hallucinated tools or arguments that don't exist?
Identify tool selection gaps before they cause production failures.
Error Classification
When an agent fails, why does it fail? badgeIA automatically classifies failures: tool selection error, argument error, reasoning error, hallucination, timeout, rate limit, or token limit exceeded. Understanding error distribution helps you prioritize improvements.
Regression Detection & Alerting
The moment you deploy an agent, degradation can begin. A model API might change its behavior. A tool's response format might shift. Your agent's confidence threshold might need adjustment. Without monitoring, these changes go unnoticed until they impact users.
badgeIA continuously benchmarks your agent at regular intervals (hourly, daily, or weekly). When performance degrades—success rate drops, latency increases, cost per run spikes, or consistency declines—we alert you automatically. Alerts include:
Success Rate Regression Alert
"Agent success rate dropped from 94% to 87% in the last 24 hours. The following test cases are now failing."
Latency Spike Alert
"P95 latency increased from 3.2s to 8.7s. This correlates with heavy retries on the SearchTool API."
Cost Anomaly Alert
"Cost per run increased 40% this week. The agent is now using 3x more tokens per execution."
Consistency Degradation
"Agent consistency dropped from 96% to 78%. The same input now produces different outcomes across runs."
Catch issues early. React before customers do. Maintain production SLAs with confidence.
Testing Capabilities
Parametric Test Cases
Define test cases with variable inputs and expected outputs. Run the same test case with different parameters to understand how your agent handles variation. Build edge case test suites (token limits, special characters, multilingual inputs, etc.).
Batch Reliability Testing
Execute a test case hundreds or thousands of times in parallel. Measure consistency, identify the distribution of failures, and understand behavior variance at scale.
Custom Success Criteria
Define what "success" means for your agent. Check exact output match, semantic similarity, or custom validation logic. Build reliability metrics aligned with your use case.
Automated Regression Testing
Continuous benchmarking runs your test suite on a schedule. Every model upgrade, prompt change, or tool update is automatically tested. Know the impact of changes before they reach production.
Detailed Execution Logs
Every agent execution is logged: all LLM calls, tool invocations, retry attempts, and error messages. Debug production failures by replaying the exact execution context.
Start Testing Your Agent's Reliability
Deploy agents with confidence. Get instant reliability metrics, automated regression testing, and alerts for performance degradation. Know your agent's real production readiness.
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