Enterprise AI security
Token savings built in
OryxAI mediates every prompt, completion, and tool invocation between your engineers and the models they rely on — enforcing policy inline, redacting sensitive data, and producing tamper-evident audit across Cursor, Claude Code, Copilot, Windsurf, and MCP agents.
Because OryxAI sits in the path anyway, it trims context tokens before they're spent: commands are rewritten at the hook, tool output is filtered at the proxy. Teams running JavaScript or Rust toolchains typically see 25–40% fewer tokens per session — with no changes to their agent workflow.
Traffic passes in and out through the same policies — nothing reaches the model or returns to the IDE unchecked.
Works alongside
Context
Assistants rewired delivery cycles before trust boundaries caught up. Point tools rarely add policy, lineage, and org-wide posture together.
Shadow adoption
Coding assistants spread team by team. Without a shared choke point, nobody knows which prompts, repos, or tool actions are effectively “approved.”
Leakage & liability
Models can echo secrets or personal data back into chat, commits, or tickets. Incident response stalls when there is no single record of what was sent or blocked.
Agent risk
Agents do not stop at autocomplete — they run commands, APIs, and file changes. Trusted-by-default tooling is brittle once production data is reachable.
One enforceable boundary
Security and platform teams define policy once; every assistant route (proxy, MCP, IDE) inherits the same rules instead of fragmented toggles.
Provable oversight
Tamper-evidence friendly audit means compliance and leadership can answer who asked what, what was altered, and which policy blocked or allowed it.
Gradual control — and a smaller bill
Start with observability (log-only) and tighten to block or approvals as you learn how teams actually ship with AI. Token savings activate the moment you route traffic through the proxy.
Efficiency
Intercepting traffic creates an opportunity: strip the noise before it reaches the model. OryxAI recovers tokens automatically at two points in the pipeline — no agent changes, no new workflow.
Typical savings
25 – 40%
fewer tool-call tokens per session in JavaScript and Rust toolchains
At $0.002 / 1K tokens, a 50-developer team running 400 tool calls a day recovers the platform cost before the month closes.
A lightweight PreToolUse hook rewrites shell commands before they execute. Verbose flags that generate walls of output are replaced with quiet equivalents — so the tool produces less, and the model reads less.
Tool output returning through the proxy is stripped of deprecation warnings, progress bars, and boilerplate before it reaches the model. No agent changes needed — it works for any API-mode client routing through OryxAI.
Both layers log to the audit trail — every token saved is traceable.
How teams ship
Pick a profile, tune modules, and attach your repos or proxy endpoint.
Issue API keys, enable MCP, or point your LLM clients at OryxAI upstream.
See decisions in audit, tune thresholds, route critical tool calls through approval.
Hosted or beside your repos — same YAML contract, same lineage.