What is a Lakera alternative?
Lakera Guard, part of Check Point, inspects prompts and outputs for injection, jailbreaks, and PII. That's content inspection. It isn't an in-code action gate, and it isn't telemetry.
The honest shortlist is by layer, not a ranked "six best" with the author first and the actual peer omitted. HiddenLayer, Pillar, and other guardrail vendors sit on the same content-inspection layer as Lakera. For a map of the category, see AI agent security platforms.
What Lakera Guard does
Lakera Guard evaluates model input and output for prompt injection, jailbreaks, policy violations, and sensitive data. Check Point announced the acquisition in 2025 and folded the product into its AI security portfolio. The detection models and the Gandalf-derived adversarial data are still what Guard sells.
That layer answers Is this text unsafe? It can block or flag content before a provider call when you send the text to the inspector (SaaS) or run a self-hosted inspector. It doesn't, by itself, authorize contacts.update with application identity, a per-user token budget, or a tool call that never leaves the process.
If you're already standardized on Check Point, staying with Lakera is a defensible choice.
Honest alternatives, by layer
| Product | Layer | What it actually is |
|---|---|---|
| Lakera Guard (Check Point) | Guardrails and content inspection | Prompt, jailbreak, and PII inspection on text you send it, SaaS or self-hosted |
| HiddenLayer, Pillar, Straiker | Guardrails and content inspection | Same job as Lakera: Is this input or output unsafe? |
| Datadog AI Guard | Observability and detection | An evaluator you call; verdicts land with the rest of your Datadog traces |
| Rein Security | In-code runtime enforcement | A code-native sidecar around the agent runtime, with business-impact mapping |
| Arcjet | In-code runtime enforcement | A check you call: |
Gateways (Runlayer, Kong, NeuralTrust) and identity products (Keycard, Aembit) also aren't Lakera substitutes. They answer sanctioned traffic and credentials. Include them in a program. Don't put them on a Lakera bake-off as if they inspect the same text.
How they differ
| Question | Lakera (Check Point) | Datadog AI Guard | Rein | Arcjet |
|---|---|---|---|---|
| Block before the side effect? | Yes, on content it inspects | Yes, when blocking is enabled in the service policy | Yes, in the sidecar path | Yes, at |
| Local inspection of the raw body? | SaaS sends text; self-host keeps it | Prompts and tool calls are sent to Datadog | Execution data stays in the org | Sensitive-info is in-process. Prompt injection and rate limiting use the Cloud API |
| HTTP and tools? | Content path you integrate | Wherever you call the evaluator | Agent runtime that the sidecar wraps | HTTP plus tools, MCP, and jobs. Guard doesn't detect bots |
| Who authors the rule? | Lakera and Check Point policy | Datadog AI Guard Settings | Configured with the sidecar | App-specific rules in code. Operational HTTP remote rules in the dashboard or MCP |
Arcjet's sensitive-information detection uses a built-in local engine plus an optional on-device NER model for names, addresses, and government or financial identifiers. The raw body is never sent. That's a claim about content inspection, not about every rule.
When a check can't finish, a direct Guard call returns allow with error codes. Vercel AI SDK and LangChain wrappers fail closed unless you opt into continuing on error. HTTP request checks can fail open when Arcjet's cloud can't be reached; that's configurable. A correlationId reconstructs a run. It doesn't change allow or deny.
When to choose which
Stay with Lakera when the job is content inspection, you want Check Point procurement, and you're satisfied sending text to Guard or self-hosting it.
Choose another guardrail (HiddenLayer, Pillar) when you want the same layer from a vendor that isn't Check Point.
Choose Datadog AI Guard when traces and detections already live in Datadog and you want an evaluator in that estate. See Arcjet vs Datadog AI Guard.
Choose Rein when you want a sidecar around the agent runtime rather than a check per code path. See Arcjet vs Rein.
Choose Arcjet when you want the deny in your application, on the HTTP route and on the tool. App-specific rules stay in code, and a security team can change operational HTTP rules without a deploy. SOC 2 Type 2 is complete (Trust Center).
You can keep Lakera for content and add Arcjet for the action. Those are different questions. A Lakera alternative that replaces only the inspector still leaves the CRM write ungated.
Learn more: Category map · Enterprise buyer page · Agent guards
Frequently asked questions
What is a Lakera alternative?
It depends which job you needed Lakera for. Lakera Guard, now part of Check Point, is content inspection. Datadog AI Guard is telemetry. Rein is the in-code sidecar peer. Arcjet is the in-code check you call. Those are different layers, not a ranked list.
Does Datadog AI Guard replace Lakera?
Not as a content-inspection substitute. Datadog AI Guard is an evaluator whose verdicts land with your traces, and it can block inline: an SDK call can request exception-based blocking, provided the remote service policy also has blocking enabled. It is still a different job than Lakera-style content inspection on text you send it.
Does Arcjet inspect content locally?
Sensitive-information detection runs in-process and the raw body is never sent. Prompt injection detection calls the Cloud API with the prompt being evaluated. Answer per control, not per product logo.
AI runtime security in your code
Protect your AI agent workflows with Arcjet
Arcjet runs inside your application, where it can use runtime context to enforce agent actions and budgets, detect prompt injection, and protect sensitive information before a workflow acts.