Architecting High-Throughput Context for Autonomous Agents
ContextRail AI provides high-speed semantic context routing, episodic memory middleware, and Model Context Protocol (MCP) streaming infrastructure built natively for Anthropic Claude (Sonnet and Haiku).
Our Mission
The critical bottleneck in autonomous agent workflows is rarely model intelligence; it is context bloat and retrieval latency. As agents execute multi-turn tasks across tools, databases, and code repositories, stuffing uncurated documents into the prompt degrades attention, increases time-to-first-token (TTFT), and escalates token costs.
ContextRail AI treats context as a dynamic routing fabric rather than a passive text bucket. By aligning dynamically pruned chunks with Anthropic prompt caching boundaries, our middleware cuts RAG token payloads by up to 78% while guaranteeing 99.4% recall on critical needle tokens.
We are a 100% developer-centric software platform: zero agency work, zero bespoke services, and zero manual consulting. All capabilities are exposed via standardized Model Context Protocol (MCP) endpoints and high-concurrency REST APIs.
Corporate Entity & Headquarters
B-88514920
https://contextrail.cloud
admin@contextrail.cloud
gregorio@contextrail.cloud
Engineering Leadership
Software engineers and systems architects dedicated to low-latency agent infrastructure.
⚡ Sub-50ms Routing
Dynamic token pruning pipelines that slice high-salience context before reaching Claude API inference, keeping agent TTFT under control.
🧩 Native MCP Card
Exposes machine-readable endpoints at /.well-known/mcp/server-card.json with 5 pre-built tools for Claude Code and Claude Desktop.
🛡️ EU Privacy & Zero Training
Zero retention policy on memory payloads. Enterprise encryption in Madrid and Frankfurt edge regions without model training on customer payloads.