ContextGeneration was born from a $63 overnight incident — an AI agent retried a failed API call 800 times because its context contained everything except what it had already done. We built the platform we wished existed.
To make AI agent context auditable, time-aware, observable, and safe to use in consequential decisions. We are building the governance layer that production AI needs — not just another RAG wrapper.
Four principles that guide every product decision we make
We believe the quality of context fed to an AI agent is the single most important factor in its performance. Every feature we build starts from this principle.
AI agents fail silently. We build observability, governance, and audit tools that make context failures visible before they become expensive mistakes.
Context engineering is already hard. Our tools should make it easier, not add more ceremony. We obsess over reducing friction at every step.
We publish our research, share our benchmarks, and build on open standards. The context engineering community grows when knowledge is shared.
Founded after observing production AI agents failing due to poor context management
Launched Context Curation Engine and Playground — first 500 users in 30 days
Introduced Context Health Monitor — first platform to score context rot in real-time
Launched Context Replay Studio, Temporal Graph, Governance, and Multi-Agent Bus
Serving engineering teams across fintech, healthcare, and legal AI applications
Whether you're building your first AI agent or managing a fleet of production agents, we have the tools to make context work for you.