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OPAQUE

Confidential AI platform that runs agentic and analytics workloads inside TEE-backed environments with verifiable attestation and policy enforcement on sensitive data.

6.3/10
Overall Score
Conditional recommend

OPAQUE is a serious confidential-AI option when TEEs and attestation are hard requirements. Pricing is sales-led with no public rate card; evidence depth is still thinner than broader privacy tools. Approach with caution for most buyers in this category.

Best for

Regulated enterprises that must run AI or analytics on sensitive data inside confidential VMs with hardware-backed attestation.

Not ideal for

Teams without TEE-capable cloud regions, or buyers that only need classic de-identification before an ordinary LLM call.

Verdict

OPAQUE is a good fit for privacy and security teams that need confidential AI with runtime attestation, not just pre-processing redaction. Pricing is enterprise and sales-quoted with no public tier table. Practitioners and partner materials emphasize TEE-backed execution and policy proofs; it is a conditional pick when confidential computing is a hard requirement rather than a nice-to-have.

Score Breakdown

How OPAQUE scores in the categories that matter to its buyers.

Buyer outcomes

Confidential AI runtime
6.6
Attestation & policy proofs
6.4
Cloud TEE deployment fit
6.2
Public evidence maturity
5.9

Company & commercial

Innovation & product leadership
6.5
Project management & communication
6.4
Pricing
5.9
Contract fairness
6.3

The Field at a Glance

Where OPAQUE ranks among Privacy & compliance vendors we reviewed, by Overall Score and relative typical engagement cost.

6 7 8 9 Overall Score $ $$ $$$ $$$$ Relative typical engagement cost Limina OPAQUE 6.3
OPAQUE Limina

OPAQUE scores 6.3 versus Limina at 5.8 in privacy & compliance. Limina is stronger for on-environment de-identification before model use; OPAQUE is the confidential-runtime / TEE path. Relative typical engagement cost for OPAQUE is higher as sales-led confidential platform work.

Use-case matrix

Use caseFitNotes
AI on encrypted / sensitive dataStrongCore confidential runtime.
Hardware attestation for auditsStrongExportable attestations.
Simple PII scrub before SaaS LLMMixedDe-id tools may be enough.
Regions without confidential VMsPoorTEE capacity is a hard gate.

Who it’s for

Good fit

  • Regulated AI programs on Azure/GCP confidential VMs
  • Teams that need verifiable policy enforcement at runtime
  • Agentic workflows over sensitive enterprise data

Poor fit

  • SMB teams without TEE budget or cloud regions
  • Buyers that only need redaction / tokenization
  • Shops that cannot run Kubernetes on confidential nodes

Review Excerpts

Below are excerpts from public reviews. Paid reviews and pay-for-play sites such as Clutch were excluded.

How it's used

“OPAQUE runs agentic AI workloads on sensitive data inside hardware-secured environments, keeping data encrypted during execution and continuously verifying that approved policies are enforced.”

Product positioning · opaque.co · source
What people like

“ServiceNow used OPAQUE’s confidential AI platform to cut commission inquiry times from days to seconds while keeping sensitive compensation data protected in use.”

OPAQUE customer story · ServiceNow · source
What people don't like

“Pricing is not publicly disclosed, which makes cost comparison difficult for mid-market buyers evaluating against open-source or pay-as-you-go alternatives.”

Independent catalog note · 7wData / Opaque Platform · source
What people don't like

“Confidential Agents require TEE-capable hardware, which may not be available in all cloud regions, potentially limiting deployment flexibility.”

Independent analysis · 7wData Confidential Agents · source

Methodology

This page is an independent evaluation of OPAQUE for buyers comparing options in privacy & compliance. AI Industry Reviews accepts no sponsorships, advertising, or pay-for-placement fees. OPAQUE did not pay for this review.

What we scored

The headline number is an Overall Score on a 0-10 scale. Eight criteria fall under it in two groups.

  • Buyer outcomes (for privacy & compliance)
    • Confidential AI runtime
    • Attestation & policy proofs
    • Cloud TEE deployment fit
    • Public evidence maturity
  • Company & commercial
    • Innovation & product leadership
    • Project management & communication
    • Pricing
    • Contract fairness

Pricing measures whether the price looks fair for the value delivered, including packaging and renewal friction that show up in real buying cycles.

Score Composition

InputWeightWhat it covers
Reviews40%A proprietary read of what practitioners say about likes, complaints, and day-to-day use, including public review sites, forums, and private chat rooms. Paid reviews and pay-for-play sites such as Clutch are out of scope.
Product35%Hands-on look at screens and workflows.
Pricing15%Whether the price looks fair for what you get.
Docs & training10%Docs, tutorials, and training material.

How we balanced the evidence

The Overall Score is the simple average of the eight criteria. Recommendation language follows that score and the fit pattern described above.

Scope

OPAQUE is graded here as privacy & compliance. Criteria scores can move as more review volume and product checks are added.

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