The Context Company builds observability tooling that monitors AI agents and helps teams understand user behavior, with a focus on detecting silent failures in production. The platform turns raw agent conversations into structured signals such as topic clustering, user feedback analysis, custom pattern tracking, and alerts, alongside traditional observability like traces, tool calls, latency, and cost. Setup requires under 10 lines of code and supports the Vercel AI SDK, LangChain, and LangGraph. The company was part of Y Combinator's Fall 2025 batch.
The Context Company
ActiveMonitor AI agents and understand user behavior
Total raised
$500K
1 round
Stage
Seed
Jan 2025
Team
1-10
since 2025
Pricing
—
Founded
2025
San Francisco, United States
Agent-ready
—
Observability tooling for AI agents
Detection of silent failures in production
Topic clustering of agent conversations
User feedback analysis
Custom pattern tracking
Alerts on detected issues
Traditional observability: traces, tool calls, latency, and cost
Setup in under 10 lines of code with SDK integrations
12/100
Early
MCP server
Public API
Webhooks
OAuth 2.0
SDKs
No public agent surfaces detected yet.
Jan 2025 Seed $500K ● Y Combinator
Capital network
$500K raised ·1 backer·10 network links
- Backers1
- Shared portfoliocompanies these backers also fund
- Extended networkfunds that co-invest alongside them
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- What does The Context Company do?
- It provides observability tooling that monitors AI agents and surfaces user behavior patterns and silent failures, turning agent conversations into structured signals like topic clusters, feedback, traces, and alerts.
- What frameworks does it support?
- Setup requires under 10 lines of code and supports the Vercel AI SDK, LangChain, and LangGraph.
- How is it different from standard observability?
- Beyond traditional traces, tool calls, latency, and cost, it focuses on detecting silent failures and structuring raw conversations into topic clustering, feedback analysis, and custom pattern tracking.
- Who is it for?
- It is built for teams running AI agents in production who need to understand user behavior and catch failures.
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