Zytra vs Lakera (Check Point): two different products for two different problems
Lakera was acquired by Check Point in October 2025. The combination places Lakera Guard inside a network security stack — adding breadth for enterprise security teams but moving further from the AI governance evidence chain that banks need for RBI, SEBI, and EU AI Act examinations.
Different origins, different outcomes
Lakera Guard was built to solve a specific problem: prompt injection and jailbreak detection at inference time. It does that well. Zytra was built to solve the broader problem banking risk teams face: how to demonstrate, with auditable evidence, that every AI system in production is governed to the satisfaction of RBI, SEBI, and EU AI Act.
These are not the same product. They are not even adjacent product categories. Runtime security is one domain in a BFSI AI governance program — and it is not the domain that drives examination findings or board-level risk reporting.
Regulatory coverage depth
| Requirement | Zytra | Lakera / Check Point |
|---|---|---|
| RBI 2024 AI Circular — audit trail, risk controls, board approval evidence | Full coverage | Not covered |
| RBI FREE-AI — 26 recommendations, Reliability + Transparency pillars | Clause-level mapping | Not covered |
| RBI eMRM 2026 — independent validation, tier classification | Full draft coverage | Not covered |
| SEBI Responsible AI — 6 principles, control-level mapping | Full coverage | Not covered |
| DPDP Act 2023 — inference-layer PII detection, consent verification | Pipeline-level | PII detection only (no consent or governance) |
| EU AI Act — risk management, technical documentation, human oversight | Art.9, Art.12, Art.14, Art.15 | Runtime security only — no governance documentation |
| SR 11-7 — model risk management, validation, MRC governance | Full + GenAI extension | Not covered |
| NIST AI RMF — GOVERN, MAP, MEASURE, MANAGE | All four functions | MANAGE only (runtime monitoring) |
| MITRE ATLAS — D-09, D-10, D-11 | All three | D-09 only (prompt injection) |
| OWASP LLM Top 10 — LLM01–LLM10 | All ten | LLM01–LLM02, LLM06 primarily |
What the acquisition means for BFSI buyers
Check Point is a world-class network and cloud security company. The acquisition gives Lakera Guard enterprise distribution and integration with a mature security ecosystem — which is valuable for security teams building a unified threat management posture.
For banking model risk managers, compliance officers, and CROs evaluating AI governance tools, the acquisition creates three practical questions:
- Roadmap uncertainty: product direction post-acquisition is driven by Check Point's enterprise security strategy, not BFSI AI governance requirements. India-specific regulatory coverage (RBI, SEBI, DPDP) is unlikely to be a roadmap priority for a global network security vendor.
- Deployment model: Lakera Guard's deployment within the Infinity platform may not satisfy RBI's single-tenant or on-premises requirements for Indian banks. Verify directly with Check Point.
- Evidence format: Check Point produces security telemetry. RBI examiners ask for governance evidence packs. These are structurally different outputs — security logs do not map directly to the evidence a regulatory examination requires.
Lakera Guard (Check Point) and Zytra solve different problems. If your primary question is "how do I add prompt injection detection to my infrastructure," Check Point's security ecosystem is worth evaluating alongside Zytra's Aval guardrail. If your primary question is "how do I produce examination-ready evidence that my AI systems are governed to RBI, SEBI, and EU AI Act standards," Zytra is the purpose-built answer — no other vendor covers all three regulatory bodies with clause-level mapping and evidence generation.
What Zytra covers that Lakera never did
Model governance lifecycle
Inventory, risk tiering, validation tracking, MRC approval, and audit-trail export. Lakera was a detection layer — never a governance system.
India regulatory evidence
RBI 2024 AI Circular, FREE-AI Framework, eMRM 2026, SEBI Responsible AI, DPDP Act — clause-level mapping with examination-ready evidence packs. No competitor covers India.
Residual risk reporting
Board-level heat maps showing inherent risk vs. control effectiveness vs. residual exposure by domain. Built for CROs and audit committees, not security operations centers.
Evaluating AI security tooling for your bank?
Zytra covers the full BFSI AI governance stack — runtime security (Aval, 22 threat categories, 0.5% FPR), governance workflows (risk atlas, MRM, evidence), and red-teaming (FinProof benchmark) — all with examination-ready output for RBI, SEBI, and EU AI Act.