vs 
Lakera guards prompts. We govern agents.
Lakera detects prompt injection and secures LLM inputs in real time. Prefactor governs whether agents produce the right outcomes at the right cost. [1]
What they do well - Real-time prompt injection and jailbreak detection with sub-50ms latency and 98%+ detection rates across 100+ languages.
- Data leakage prevention: PII detection, system prompt leakage prevention, sensitive data filtering inline.
- Content moderation: toxicity, harmful content, and malicious link detection in real time.
- Lakera Red: automated adversarial red teaming against LLM applications before and during production.
- Gandalf threat intelligence: 80M+ adversarial prompts from 1M+ players feeding continuous model updates — an industry-unique threat intelligence source.
- API-first, low-latency, minimal integration friction — add a single API call.
- Gartner Representative Vendor in AI TRiSM. Now part of Check Point's Infinity Platform.
Best for: engineering teams that need fast, accurate, low-latency prompt/response security for LLM-powered applications — particularly customer-facing deployments.
What we do - Outcome quality assessment: did the agent produce the right result for the task it was deployed to complete?
- Cost efficiency assessment: was the spend proportionate to the result?
- Scope adherence: did the agent stay within its approved boundaries, tools, and actions?
- Composite risk score from these signals, with customer-set thresholds that determine what happens next.
- Inline blocking and approval routing when risk thresholds are crossed.
- Agent registry and lifecycle governance from registration through retirement.
- Immutable audit log for regulatory review.
Best for: AI leadership, AI governance, compliance, and enterprise architecture teams that need continuous operational governance of production agents.
Lakera: the prompt/response layer
- Inspects every input going into an LLM and every output coming out
- Real-time, sub-50ms latency
- Stops bad things happening at the model interaction level
- Asks: is this prompt safe?
Prefactor: the agent layer
- Governs agents as operational entities across runs
- Assesses whether agents complete their intended tasks correctly and cost-efficiently
- Enforces controls when agents drift from approved scope
- Asks: is this agent performing as intended and worth the investment?
A well-architected production AI system might use Lakera to secure individual LLM interactions and Prefactor to govern the agents that orchestrate those interactions. These layers are different and complementary — Lakera is built for developers with single API call integration, while Prefactor is built for AI leadership and governance teams managing agent fleets across the organisation.
| Capability | | |
|---|---|---|
| Overview | ||
| Primary layer | Prompt/response level | Agent level |
| Primary buyer | Engineering teams | Head of AI, AI Governance, Enterprise Architecture |
| Security capabilities | ||
| Prompt/response security | ✓ | — |
| Real-time LLM guardrails | ✓ | — |
| Adversarial red teaming | ✓ | — |
| Governance & operations | ||
| Outcome quality assessment | — | ✓ |
| Cost efficiency tracking | — | ✓ |
| Composite risk scoring | — | ✓ |
| Agent-level inline blocking | — | ✓ |
| Configurable approval routing | — | ✓ |
| Enterprise readiness | ||
| Agent registry and lifecycle | — | ✓ |
| Compliance audit trail | ◔ | ✓ |
| Regulated industry design | ◔ | ✓ |
| Integration approach | Single API call per LLM interaction | Platform-level governance layer |
Related: Prefactor for ML Engineering
Prompt security and agent governance
Lakera secures the LLM interaction layer. Prefactor governs the agents that orchestrate those interactions. Together they cover both layers.
Book a demo View all comparisonsFrequently asked questions
What happened to Lakera?
Lakera was acquired by Check Point Software in September 2025 to form Check Point's Global Center of Excellence for AI Security. Lakera Guard and Lakera Red remain available as standalone products and are being integrated into Check Point's Infinity Platform and CloudGuard WAF.
Does Prefactor do what Lakera does?
No. Lakera operates at the prompt and response layer — inspecting individual LLM inputs and outputs in real time for security threats. Prefactor operates at the agent layer — governing agent deployments as operational entities, assessing their performance and cost efficiency, and enforcing governance controls. They address different parts of the AI security and governance stack.
Can you use Lakera and Prefactor together?
Yes — and this is a natural pairing. Lakera secures individual LLM interactions at the prompt/response layer. Prefactor governs the agents that orchestrate those interactions at the operational layer. Together they provide both prompt-level security and agent-level governance.
How We Reviewed This Comparison
This page was reviewed against public product and documentation pages on March 19, 2026. If a vendor has changed a feature, product name, or positioning since then, send a correction and we will update the comparison.
Numbered source links in the page body point to the ordered public sources below.
Sources reviewed
Prefactor contextMethodology
- Reviewed public product, documentation, and launch material visible at the time of writing.
- Mapped each page to the primary buyer, control layer, and runtime capabilities each vendor describes publicly.
- Prefer direct product and documentation pages over analyst summaries or reseller material.