Build Reliable AI Agents, Faster

The all-in-one platform to debug, test, and monitor AI agents—so you can deploy with confidence.

Product Research Agent

Completed
10:45 AM · 1m 23s

Execution Steps

Initial Promptprompt
10:45:01

Find the top 3 competitors for our new AI-powered analytics dashboard and compare their features.

Information Gatheringinfo
10:45:10

Collecting data on analytics dashboard providers with AI features.

Semantic Searchsearch
10:45:22

Searching for "top AI analytics dashboard competitors features comparison"

Decision Makingdecision
10:45:45

Identified Tableau, Power BI, and Looker as top competitors based on market share and feature set.

Final Responseanswer
10:46:24

The top 3 competitors are: 1. Tableau: Strong visualization but limited AI capabilities 2. Power BI: Good Microsoft integration with growing AI features 3. Looker: Strong data modeling with recent AI enhancements

Agent Runs

All Runs
Completed
Failed
NameStatusTimeDurationActions
Product Research AgentCompleted10:45 AM1m 23s
Customer Support AgentRunning10:30 AM2m 10s
Market Analysis AgentFailed10:15 AM45s
Product Research AgentRunning10:00 AM1m 30s
Customer Support AgentRunning9:45 AM2m 10s
Market Analysis AgentFailed9:30 AM45s
AI Agent Debugging Platform
Platform Background

Trace Every Step, Debug Faster

Step-by-step visibility into every agent decision, from prompt to response, allowing you to quickly identify and resolve issues.

  • Visualize the complete execution path
  • Inspect RAG retrievals and tool calls
  • Identify problematic steps instantly
  • Debug complex agent interactions
Agent Debugger
Workflow Executions
wf-1234completed
2m ago1.2s
wf-1233failed
5m ago0.8s
wf-1232completed
10m ago2.1s
wf-1231completed
15m ago1.5s
Execution Trace
User Input0.0s
How do I reset my password?
Agent Planning0.2s
Determining steps to help with password reset
Knowledge Retrieval0.4s
Retrieved 3 documents about password reset procedures
Context Formation0.5s
Compiled knowledge base and user context
API Tool Call0.7s
Attempted to call auth.checkUserStatus()
Error Handling0.8s
Fallback to general instructions without user verification
Response Generation1.0s
Generated password reset instructions
Tool Call Failed
auth.checkUserStatus(): Invalid API key provided. Check your configuration or environment variables.
Recommendation: Update API key in environment settings
Parameter Tuning
0.3
30%
50%
Response Preview

The analysis of quarterly financial data reveals:

  • Revenue increased by 26% year-over-year
  • Customer acquisition cost decreased by 15%
  • Net profit margin improved to 18%
Response Quality: 60%

Experiment Faster, Tune Smarter

Rapidly iterate on prompts and parameters to optimize performance, with real-time feedback to guide your improvements.

  • Test different parameter combinations instantly
  • Visualize how changes affect responses
  • Fine-tune prompts for better performance
  • Compare experiments side by side

Test Continuously, Deploy Confidently

Automated test suites catch issues early, ensuring your AI agents meet quality standards before reaching production.

  • Run comprehensive test suites automatically
  • Test for accuracy, safety, and robustness
  • Create custom test scenarios for edge cases
  • Get instant alerts when tests fail
Automated Test Suite
Accuracy
Safety
Robust
Custom
Live Monitoring Dashboard
Last updated: Just now
Agent Accuracy
92%
System Health
98%

Proactive Monitoring, Instant Alerts

Real-time anomaly detection and intelligent notifications keep you ahead of potential issues before they impact users.

  • Track key metrics in real-time dashboards
  • Detect anomalies with advanced algorithms
  • Receive intelligent, actionable alerts
  • Analyze performance trends over time

Developer-Friendly, Enterprise-Ready

Built for fast-moving dev teams with enterprise-grade security and scalability.

Enterprise Security
SOC 2 compliance and end-to-end encryption
GDPR & HIPAA Compliant
Meet strict regulatory requirements
OpenTelemetry Compatible
Integrate with your existing observability stack
agent.py
from evalbase import configure_telemetry, workflow, step, StepType
# Decorators at request level and for various sub-tasks
class MyAgent(Agent):
def __init__(self):
self.model = "gpt-4o"
@workflow
def handle_request(self, query):
# Top-level request monitoring
answer = self._llm_query(query)
return answer
@step(type=StepType.LLM)
def _llm_query(self, prompt):
# Measure prompt-to-response steps
return "LLM answer"
@step(type=StepType.SEMANTIC_SEARCH)
def _semantic_search(self, query):
# Track retrieval steps
return ["doc1", "doc2"]

Integrate in Minutes, Not Weeks

Seamlessly plug into your workflow with just a few decorators, and get immediate insights.

Integration Steps
1

Create an account & get your API key

Sign up at Evalbase and grab your unique API key from the dashboard.

2

Add decorators to key methods

Instrument your LLM calls, tool usage, or retrieval steps with a single decorator.

3

Start monitoring your agent

Enjoy real-time traces, performance metrics, and debugging insights.

Start Building Better AI Agents Today

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