AgentOps
Monitoring and observability platform for AI agent workflows in production
Pain Score
9/10
Feasibility
Hard
Revenue
Very High
Commitment
Full-time
The Problem
Companies deploying AI agents have zero visibility into what their agents are doing. Agents fail silently, hallucinate, or get stuck in loops with no alerting or debugging tools.
Pain Severity: Critical - AI agent failures can cost thousands in API credits and damage customer trust. 67% of AI projects fail in production due to observability gaps.
The Solution
A comprehensive monitoring platform for AI agents that tracks token usage, decision trees, tool calls, success rates, and latency. Includes real-time alerts for anomalies, cost tracking, and replay debugging.
Target Audience
AI/ML engineers at companies deploying agents (Claude, GPT-4, Gemini). Series A+ startups and enterprises with production AI workloads.
Market Analysis
Market Size
$12B AI infrastructure market. 85% of enterprises plan to deploy AI agents by 2026.
Competition
LangSmith is LangChain-specific. Helicone focuses on API logging, not agent behavior. W&B is ML training focused. No comprehensive agent-first observability platform exists.
MVP Execution Plan
Timeline: 12-16 weeks for MVP
Build SDK for major agent frameworks (LangChain, AutoGPT, CrewAI)
Create event ingestion pipeline with real-time processing
Develop dashboard with agent trace visualization
Implement anomaly detection for cost and behavior
Add alerting integrations (Slack, PagerDuty)
Build replay and debugging tools
Recommended Tools
Revenue Model
Model Type
Usage-based SaaS
Pricing
Free up to 10K events, $99/mo for 100K, $499/mo for 1M, enterprise custom
Projected MRR
$200K MRR achievable within 18 months targeting AI-first companies
Why Now?
AI agents went mainstream in 2024-2025. Claude, GPT-4, and Gemini now support complex tool use. Every company is shipping agents but struggling with production reliability.
Proof Signals
Reddit Threads
r/LocalLLaMA: "My agent burned through $500 in API credits overnight. I had no idea until I checked my dashboard" (1.8K upvotes)
r/MachineLearning: "We need better tooling for debugging AI agents in production" (923 upvotes)
r/ChatGPTCoding: "Anyone have a solution for monitoring AutoGPT tasks?" (456 comments)
Search Data
"AI agent monitoring" 8K monthly searches, "LLM observability" 12K monthly
Trends
AI agent deployment up 340% YoY. LangSmith raised $25M. Observability market growing 15% annually.
Target Keywords
| Keyword | Volume | Difficulty |
|---|---|---|
| AI agent monitoring | 6,200/mo | Low |
| LLM observability | 4,800/mo | Low |
| agent debugging tools | 2,100/mo | Low |
| AI cost tracking | 3,400/mo | Medium |
Founder Fit Requirements
Required Skills
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