MoorAI reviews prompts and responses on the device — content never leaves the machine, and it wraps the AI agents you already run: Claude Code, Codex, GitHub Copilot CLI. MoorAI does inspect the prompt and the model's reply against policy — but locally, before anything is sent, so the inspection itself never becomes egress. Security teams see only redacted, content-free signals — a category, a risk level, a one-way hash. The difference from Forcepoint is not whether prompts and responses are inspected; it is where they are inspected and what leaves the machine. Open source (AGPL-3.0).
Forcepoint AI Data Security is a data-centric DLP platform that governs an organization's whole AI estate by inspecting prompts and responses in real time, discovering shadow AI across apps and browser extensions, and enforcing policy on agent MCP traffic through an inline AI Agent Gateway — with natural-language policy authoring (ARIA) and a single console over ChatGPT, Claude, and Copilot for Enterprise. This is an honest, architecture-level comparison: a narrow, content-free on-device tool versus a broad platform that inspects the content. The two are more complementary than competitive.
The distinction below is not about either vendor's feature list — Forcepoint's DLP and classification are mature and broad. It is about where the prompt gets inspected, and what reaches a console: the actual content in a vendor's platform, or a category, risk level, and hash on the machine where the prompt was typed.
The questions every AI-governance buyer is being asked. These are the five questions the market — Forcepoint included — now puts to security leaders. They are the right questions. Here is how MoorAI answers each one without the prompts ever leaving the device.
Forcepoint and MoorAI operate at different scopes. Forcepoint AI Data Security is a consolidated, data-centric platform — DLP, DSPM, DDR, shadow-AI discovery, real-time prompt/response inspection, and an inline AI Agent Gateway — that governs AI activity across an organization from a single console. MoorAI does one thing: it reviews the prompts a developer sends to a coding agent, locally on that developer's machine, before anything is sent — so prompt content is never inspected off the device.
| MoorAI | Forcepoint AI Data Security | |
|---|---|---|
| Where prompts are reviewed | On the device, before send | Inspected inline (prompt & response) |
| Prompt / response content leaves the machine | Never — content-free by construction | Inspected & classified to enforce policy |
| What reaches the console | Category, risk level, one-way hash | Full content inspection & DLP incidents |
| Reviews prompts AND responses | ✓ on-device, content-free | ✓ content-based, inline |
| Scope | AI coding agents on the developer's machine | Org-wide: SaaS, browser, enterprise AI apps, agents |
| Deployment model | Self-hosted, on-device | Cloud-delivered platform + endpoint agents |
| Coding-agent handling | Wraps the CLI / PTY on-device | MCP traffic via the inline AI Agent Gateway |
| MCP tool-call interception (arguments) | ✓ On-device, before the call runs | Inline via the AI Agent Gateway |
| On-device AI Agent Gateway | ✓ Named chokepoint · content-free per-call ledger (Claude Code) | Inline AI Agent Gateway (org-wide) |
| Blocks secrets read into agent context | ✓ Claude Code hooks · Codex / Copilot CLI detect-only | — |
| Reviews AI output, not just prompts | ✓ Output-stage detectors + CLI redaction | Yes — inline, both directions |
| Shadow-AI / agent discovery | ✓ On-device app + browser-extension discovery + AIBOM | Org-wide, across apps & browser extensions |
| Browser-AI coverage | ✓ Companion extension, content-free | Org-wide, content-based |
| Natural-language policy authoring | ✓ authoring-time compile, deterministic runtime | Yes — ARIA (plain-English → policy) |
| Content-free compliance evidence | ✓ Signed decisions, AIBOM, framework packs | Content-based DLP reporting |
| Runs fully on-device (no egress) | ✓ Always | Cloud-delivered platform |
| Licensing | Open source (AGPL-3.0) | Proprietary |
| Account required to start | No (community agent) | Enterprise platform |
The honest take. Forcepoint AI Data Security is genuinely strong at breadth — mature DLP and data classification, org-wide shadow-AI discovery across SaaS and browsers, natural-language policy authoring with ARIA, and inline enforcement in both directions from one console. If your requirement is a single platform inspecting all AI traffic across the whole company, that is its home ground. MoorAI is deliberately narrower — content-free, on-device guardrails for the coding agents your developers run, so prompt content never passes through a vendor at all, and it is open source. And we are precise about that narrowness: MoorAI’s on-device MCP gateway governs Claude Code today — via its PreToolUse hooks — while Codex and Copilot CLI are detection-only, because those CLIs expose no equivalent enforcement hook yet. Where “the prompt cannot leave the machine” is a hard line, MoorAI sits below the gateway rather than replacing it.
Forcepoint capabilities described here are drawn from Forcepoint's own published material (the AWARE “Decoding Agentic AI Security” program and Forcepoint AI Data Security product pages) and reflect its stated architecture. Forcepoint, ARIA, and AI Data Security are trademarks of Forcepoint LLC; this page is not affiliated with or endorsed by Forcepoint. Comparison is architecture-level — verify current specifics against each vendor's docs. A “—” cell means we could not confirm the capability either way from published material; it is not a claim that the capability is absent.
Recently shipped in MoorAI — all on-device and content-free: a lethal-trifecta detector, rules-file poisoning detection (CLAUDE.md / .cursorrules), a capture-tier toggle (content-free by default), per-tool MCP argument rules, a per-agent assurance score, a data-lineage / Event Flow view, on-device model escalation, just-in-time elevation, and cryptographically signed agency decisions — mapped across OWASP LLM Top 10, NIST CSF, NIST AI RMF, SOC 2, ISO 27001/42001, and the EU AI Act.