import { Activity, Brain, DollarSign, ArrowRight, CheckCircle2, GitBranch, Cpu, Zap, } from "lucide-react"; export default function HomePage() { return (
{/* Hero Section */}
Agent Observability Platform

AgentLens

See why your AI agents make the decisions they make.
Complete observability for multi-agent systems.

View Source
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Everything you need to understand your agents

From decision trees to cost intelligence, get complete visibility into how your AI systems operate

{/* Feature 1: Decision Trees */}

Decision Trees

Visualize the complete reasoning behind every agent choice. See the branching logic, alternatives considered, and the path chosen.

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Context Awareness

Monitor context window utilization in real-time. Track what's being fed into your agents and what's being left behind.

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Cost Intelligence

Track spending per decision, per agent, per trace. Get granular insights into where every dollar goes in your AI operations.

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Python SDK

Instrument your agents in minutes

Our Python SDK integrates seamlessly with LangChain, OpenAI, and custom agents. Add observability without changing your architecture.

    {[ "Drop-in decorators for automatic tracing", "No code changes required for LangChain", "Async-first design with minimal overhead", "Type-safe with full IDE support", ].map((feature, i) => (
  • {feature}
    • ))}
{/* Code Block */}
example.py 
                
                  from agentlens import init, trace
                  

                  

                  # Initialize AgentLens
                  

                  init(
                  

                      api_key="your-api-key",
                  

                      endpoint="https://agentlens.vectry.tech"
                  

                  )
                  

                  

                  # Trace your agent function
                  

                  @trace(name="research-agent")
                  

                  async def research(topic: str):
                  

                      # Your agent logic here
                  

                      return f"Researching: {"{topic"}"
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); }