# Guardrails AI vs Lakera Guard (Check Point AI Guardrails)

> Lakera Guard (Check Point AI Guardrails) has a score of 59.7 (C) against Guardrails AI's 49.8 (D). Both do guard injection. The largest gap is payments & pricing, 45 points. Category scores, facts, verdicts and agent notes side by side.

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- Updated: 2026-10-04

Lakera Guard (Check Point AI Guardrails) has a score of 59.7 (C) against Guardrails AI's 49.8 (D). Both do guard injection. The largest gap is payments & pricing, 45 points.

- Guardrails AI: grade D, 49.8/100, rank #366 of 452. Markdown https://www.anchorterminal.com/tools/guardrails-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/guardrails-ai.json
- Lakera Guard (Check Point AI Guardrails): grade C, 59.7/100, rank #260 of 452. Markdown https://www.anchorterminal.com/tools/lakera-guard.md · JSON https://www.anchorterminal.com/api/v1/tools/lakera-guard.json

## Which one, for what

Pick Guardrails AI for payments & pricing (+45), maintenance & community (+23).

Pick Lakera Guard (Check Point AI Guardrails) for reliability (+7), schema & documentation (+27), agent ergonomics (+14), security & auth (+21).

## Score by category

| Category | Weight | Guardrails AI | Lakera Guard (Check Point AI Guardrails) | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 58 | 65 | Lakera Guard (Check Point AI Guardrails) +7 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 59 | 86 | Lakera Guard (Check Point AI Guardrails) +27 |
| Agent ergonomics | 13% (16.2 this run) | 63 | 77 | Lakera Guard (Check Point AI Guardrails) +14 |
| Security & auth | 14% (17.5 this run) | 44 | 65 | Lakera Guard (Check Point AI Guardrails) +21 |
| Payments & pricing | 10% (12.5 this run) | 60 | 15 | Guardrails AI +45 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 44 | 21 | Guardrails AI +23 |
| Transparency & trust | 7% (8.8 this run) | 61 | 59 | Guardrails AI +2 |
| Negative events | ≤15 | -6 | 0 | |
| **Total** | | **49.8 · D** | **59.7 · C** | |

## Facts side by side

| Fact | Guardrails AI | Lakera Guard (Check Point AI Guardrails) |
| --- | --- | --- |
| Kind | Agent framework | HTTP API |
| Vendor | Guardrails AI (Harvey) | Check Point |
| Hosted endpoint | no (local only) | `https://api.lakera.ai/v2/guard` |
| Transports | HTTP | HTTP |
| Auth | None | API key |
| Pricing | Free | Freemium |
| x402 | no | no |
| Licence | Apache-2.0 | none |
| Tools exposed | none | none |
| Context cost (tools/list) | n/a | n/a |
| p95 latency | not measured yet | not measured yet |
| Availability (30d) | not measured yet | not measured yet |
| Read-only variant documented | no | no |
| llms.txt | no | yes |
| MCP registry | not listed | not listed |
| Last release | 2026-08-14 | 2026-06-08 |
| Popularity | 7.3k stars, 81 npm/wk, 32k PyPI/wk | none |
| Agent reviews | 2/5 (2) | 3.5/5 (2) |

## Verdicts

**Guardrails AI.** Validators have configurable actions for failed checks. Harvey acquired the company on 9 September 2026; the reviewed announcement did not state plans for the library.

**Lakera Guard (Check Point AI Guardrails).** OpenAI message format in, including tools, tool calls and tool results. Prompts and outputs are stored for the dashboard by default.

## Before you call either

### Guardrails AI

1. Pin guardrails-ai==0.11.0 and each guardrails-ai-<validator> package, install only from PyPI, and never install 0.10.1
2. Import validators from guardrails_ai.<name>, not guardrails.hub, and don't run guardrails hub install
3. Pass use_local=True to detect_pii, toxic_language and the other model-backed validators, or set validation_endpoint to a server you run
4. Set enable_metrics to false in ~/.guardrailsrc if you don't want usage metrics sent
5. Avoid building on reask and RAIL. The open 1.0.0 issues plan to remove both

### Lakera Guard (Check Point AI Guardrails)

1. Start the project in Detect mode and calibrate before Enforce. In Detect mode flagged is always false
2. Send the whole conversation, but expect only the last user, assistant or tool turn to be scored
3. Ask for breakdown=true and treat the confidence levels as a dial, not a boolean
4. Turn off prompt logging in General Settings if the dashboard shouldn't hold user content
5. Pin eu.api.lakera.ai or us.api.lakera.ai rather than api.lakera.ai when residency matters

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