Enkrypt AI vs HiddenLayer AISec Platform 2.0

Enkrypt AI vs HiddenLayer AISec Platform 2.0: side-by-side comparison of two memory governance, privacy & safety systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.

Enkrypt AI · HiddenLayer AISec Platform 2.0

Where they differ (8)

Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.

Enkrypt AIHiddenLayer AISec Platform 2.0
TypeThree-point RAG / memory pipeline guardrailsModel Genealogy + AIBOM (supply-chain layer)
Created2022 (founded 2022 by Sahil Agarwal and Prashanth Harshangi; Yale PhDs)2022-03 (founded March 2022; emerged from stealth July 2022 with $6M seed; Series A $50M Sep 2023)
Pricingfree starter + pay-as-you-go; Enterprise: contact salesenterprise pricing; contact sales; no public pricing
Funding$2M Seed · 2024-02$56M total ($6M seed Ten Eleven Ventures Jul 2022; $50M Series A M12+Moore Strategic Sep 2023)
DeploymentREST API SaaS (cloud-hosted); no self-host option confirmedSaaS cloud or on-prem enterprise; agentless; no weights or training data access needed
MCPYes — MCP Hub: vulnerability scanning for MCP (Model Context Protocol) servers; source-based + hosted scans; MCP RegistryYes — Agentic and MCP Security use-case (Use case 04); protects agents and MCP-based systems from prompt injection / unsafe tool use
A2Ano data — searched enkryptai.com, enkryptai.com/platform/capabilities/ai-risk-removal, docs.enkryptai.com; A2A protocol not advertisedno data — searched hiddenlayer.com, hiddenlayer.com/platform, docs.hiddenlayer.com; A2A protocol not advertised
OpenTelemetryno data — searched enkryptai.com, docs.enkryptai.com; OpenTelemetry export not advertisedno data — searched hiddenlayer.com/platform, docs.hiddenlayer.com; OpenTelemetry export not advertised

At a glance

Enkrypt AIHiddenLayer AISec Platform 2.0
SectionMemory governance, privacy & safety Memory governance, privacy & safety
TierT1 T1
TypeThree-point RAG / memory pipeline guardrails Model Genealogy + AIBOM (supply-chain layer)
Created2022 (founded 2022 by Sahil Agarwal and Prashanth Harshangi; Yale PhDs) 2022-03 (founded March 2022; emerged from stealth July 2022 with $6M seed; Series A $50M Sep 2023)
Pricingfree starter + pay-as-you-go; Enterprise: contact sales enterprise pricing; contact sales; no public pricing
Funding$2M Seed · 2024-02 $56M total ($6M seed Ten Eleven Ventures Jul 2022; $50M Series A M12+Moore Strategic Sep 2023)
Backend storagecustom custom
DeploymentREST API SaaS (cloud-hosted); no self-host option confirmed SaaS cloud or on-prem enterprise; agentless; no weights or training data access needed
API surfaceREST (typical SaaS REST + first-party SDK pattern; see vendor docs for language coverage) REST (typical SaaS REST + first-party SDK pattern; see vendor docs for language coverage)
Embeddinglocked locked
Multi-tenancyhard-isolation hard-isolation
MCPYes — MCP Hub: vulnerability scanning for MCP (Model Context Protocol) servers; source-based + hosted scans; MCP Registry Yes — Agentic and MCP Security use-case (Use case 04); protects agents and MCP-based systems from prompt injection / unsafe tool use
A2Ano data — searched enkryptai.com, enkryptai.com/platform/capabilities/ai-risk-removal, docs.enkryptai.com; A2A protocol not advertised no data — searched hiddenlayer.com, hiddenlayer.com/platform, docs.hiddenlayer.com; A2A protocol not advertised
OpenTelemetryno data — searched enkryptai.com, docs.enkryptai.com; OpenTelemetry export not advertised no data — searched hiddenlayer.com/platform, docs.hiddenlayer.com; OpenTelemetry export not advertised
Optimised forgovernance + compliance + audit + adversarial hardening governance + compliance + audit + adversarial hardening
Anti-fitnot for hobbyist / non-production use cases not for hobbyist / non-production use cases

Taxonomy

AxisEnkrypt AIHiddenLayer AISec Platform 2.0
storagen/an/a
retrievalinjectionn/a
persistencesessionlong-term
updateread-onlyread-only
unitpolicymodel
governanceauditableauditable
conflictn/an/a

Pros & cons

Enkrypt AI

Pros: Comprehensive AI security product covering training data, model, and runtime — broader than memory but addresses memory-specific threats too.

Cons: Memory is one of many concerns; less depth on memory-injection attacks than Lakera.

HiddenLayer AISec Platform 2.0

Pros: Strong on adversarial ML threats (model evasion, training-data poisoning) extending into memory poisoning at runtime.

Cons: Broad ML-security positioning means memory specifically isn't the focus; pricing is enterprise-tier.

Rows last verified 2026-05-14 / 2026-05-14. Data is CC-BY-4.0 — see how to read this.