The Context Company - Catch Silent AI Failures Before They Break Production
Full observability for AI agents, from bad tool calls, loops, and hallucinations to latency and cost, in 10 lines of code.
What is up! We’re Arman and Rohil - cofounders of The Context Company
TL;DR
Setup takes under 10 lines of code, and we now support Vercel AI SDK, LangChain, and LangGraph, with more frameworks coming fast.
Our Ask
- If you’re building with Vercel AI SDK, LangChain, or LangGraph, use The Context Company for observability.
- Setup takes just a few lines - DM us on Bookface or Slack, or email founders@thecontext.company, and we’ll personally onboard you in 15 minutes.
- Not using those frameworks yet? Tell us what you’re building with, and we’ll add support fast.
The Problem
AI agents often fail quietly. Traditional observability tools only show latency or stack traces. They miss the silent layer of failures that happen inside reasoning steps or tool calls.
Most teams end up waiting until users report issues, and by then, it’s already too late. As a developer, I know you’ve been there scrolling through endless logs, trying to piece together what an agent actually did and why it failed (because trust us, we have too 🙏🏽).
We’re rethinking observability from the ground up and making silent failures a first-class primitive in agent monitoring.
Our Solution:
Instead of just visualizing traces, we analyze them and detect reasoning breakdowns across runs. In addition to traditional metrics like latency, cost, and token usage, The Context Company surfaces failures in a clean, developer-friendly dashboard.
And we’ve gone beyond the cloud:
You can now run our developer package locally to debug traces on your machine, even when you’re offline or iterating fast.
Our Progress
- Framework support: Vercel AI SDK, LangChain, and LangGraph.
- Instant setup: <10 lines of code - no refactoring or modifying your agent needed. This is what it looks like:
- Local debugging: Run observability locally on your laptop for real-time trace analysis.
- Dashboards: Full visibility into agent runs, tool calls, latency, costs, and semantic failures.
The Team
Arman and Rohil have been best friends since 6th grade (8+ years now!).
Arman optimized the public-facing AI agent at Mintlify, where he cut failure rates by 82%, and worked with enterprise design partners to build custom agents. Rohil worked on Gmail Intelligence at Google, reducing hallucinations in intent detection by 27% across 26B+ daily emails.
P.S. Even if you’re not using AI SDK, LangChain, or LangGraph, we’re adding support for other frameworks soon. Tell us what you need 😎
Dashboard:
