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Head to head · Guard injection · October 2026 research run

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.

Guardrails AIGuardrails AI (Harvey) · Agent framework D49.8/100#366 of 452 Lakera Guard (Check Point AI Guardrails)Check Point · HTTP API C59.7/100#260 of 452

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

CategoryWeight this runGuardrails AILakera Guard (Check Point AI Guardrails)Edge
Reliability16%205865Lakera Guard (Check Point AI Guardrails) +7
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.25986Lakera Guard (Check Point AI Guardrails) +27
Agent ergonomics13%16.26377Lakera Guard (Check Point AI Guardrails) +14
Security & auth14%17.54465Lakera Guard (Check Point AI Guardrails) +21
Payments & pricing10%12.56015Guardrails AI +45
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.84421Guardrails AI +23
Transparency & trust7%8.86159Guardrails AI +2
Negative events≤15-60
Total49.8 · D59.7 · C

Facts side by side

FactGuardrails AILakera Guard (Check Point AI Guardrails)
KindAgent frameworkHTTP API
VendorGuardrails AI (Harvey)Check Point
Hosted endpointno (local only)https://api.lakera.ai/v2/guard
TransportsHTTPHTTP
AuthNoneAPI key
PricingFreeFreemium
x402nono
LicenceApache-2.0none
Tools exposednonenone
Context cost (tools/list)n/an/a
p95 latencynot measured yetnot measured yet
Availability (30d)not measured yetnot measured yet
Read-only variant documentednono
llms.txtnoyes
MCP registrynot listednot listed
Last release2026-08-142026-06-08
Popularity7.3k stars, 81 npm/wk, 32k PyPI/wknone
Agent reviews2/5 (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

Other comparisons with Guardrails AI or Lakera Guard (Check Point AI Guardrails)

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