The Context Company

About

We analyze every conversation between your customers and your AI agent to find what's losing you customers and money. Then we help ship the fix and prove it worked. Nobody on the team can read every conversation once an agent is in production. TCC does, and turns them into patterns tied to the accounts they affect: where customers get stuck, what they wish the agent could do, and where it's spending more than it needs to. Engineers ask about a pattern from their IDE through our MCP, get the conversations and traces behind it down to the tool call or prompt that went wrong, ship the fix, and benchmark cost and quality before and after. Product sees what customers are actually trying to do with the agent and where it falls short, broken out by topic and account, which becomes the backlog for what to build next. Customer success sees which accounts the agent is struggling with before the customer says anything, and steps in with the full conversation on hand. Any agent framework, a few lines of code. If you're running an agent in production or about to launch, ping us.

Founders

• 
  Arman Kumaraswamy· Founder

  Cofounder at The Context Company, extending traditional AI agent observability to uncover silent failures. Previously studied CS+Math at UF, built and hyperoptimized AI agents at Mintlify (W22), and was one of the first engineers at RevisionDojo (F24). I've been in love with startups since I was in high school :)

  LinkedIn ↗Twitter ↗
• 
  Rohil Agarwal· Founder

  What is up! Previously studied EECS + Business at UC Berkeley M.E.T. and worked on Gmail Intelligence at Google, where I built models powering intent detection for 26B+ daily emails. Now building The Context Company, where we are powering developers to ship AI agents they can trust. I'm excited about solving context engineering 🙃 Oh, and I take one selfie every day!

  LinkedIn ↗Twitter ↗

Product launches · 1 launch

• The Context Company - Catch Silent AI Failures Before They Break Production ↗▲ 34Oct 27, 2025

  Full observability for AI agents, from bad tool calls, loops, and hallucinations to latency and cost, in 10 lines of code.

Change history · 7 recorded

1. September 7, 2026
   • Description rewritten07:00 PM
   • Pitch updated07:00 PM
   • Tags updated07:00 PM
2. July 15, 2026
   • Tags updated07:00 PM
   • Website updated07:00 PM
3. June 30, 2026
   • Website updated07:00 PM
   • Tags updated07:00 PM