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LEGAL AI · INTEL TDX vs LUMINANCE PROPRIETARY LLM

VoltageGPU vs Luminance

VoltageGPU is broader than M&A diligence, nine vertical agents covering sovereign legal work, contract analysis, due diligence, compliance, medical records, tax, HR, financial analysis and cybersecurity. Luminance is deeper in M&A diligence specifically. Different scopes, different optimization targets.

Luminance built their own legal LLMs instead of wrapping OpenAI, that is a real technical moat and worth respecting. The trade-off is where those models run: a standard UK/EU cloud where the operator retains read access. VoltageGPU optimizes a different axis. Our agents use open-weight TEE models (Qwen3.5-397B-TEE, DeepSeek-V3.2-TEE) that run inside Intel TDX enclaves, with a French operator on the contract; the agents themselves run on our servers, which see the documents in clear.

Headline pricing

Monthly plan price by tier. On VoltageGPU plans the model runs in an Intel TDX enclave at our inference provider; the agent runs on our servers, which see the documents in clear. A dash means the competitor does not publish a comparable per-month tier (annual contract / RFP only). Plans stay in sync with /pricing.

TierVoltageGPU (TDX agents)Luminance
Solo / single workflow
Confidential Agents, Starter
$349/mo · 1 agents · 3 seats · Contract Analyst agent, 500 reviews/mo, Qwen3.5-397B-TEE (256K ctx), model in Intel TDX, API + web UI
Luminance Corporate AI, entry
$3K/mo · 5-seat minimum · Proprietary LLM, Contract review UI, Multi-language, no TDX, no GPU TEE · RFP only, annual commit, ~$36K/year typical
Mid-market / multi-agent
Confidential Agents, Professional
$1.2K/mo · 9 agents · 10 seats · All 9 vertical agents (Sovereign Legal AI, Contract, Due Diligence, Compliance, more), 5,000 reviews/mo, Qwen3.5-397B-TEE (256K ctx), model in Intel TDX, BYOA via OpenClaw/CrewAI
Luminance Diligence
$6.3K/mo · 15-seat minimum · Diligence workflow, Autopilot autonomous review, Anomaly detection · RFP only, annual contract (~$75K/year)
Enterprise / unlimited
Confidential Agents, Enterprise
$3.5K/mo · 999 agents · 999 seats · DeepSeek-V3.2-TEE reasoning, Unlimited reviews, SSO, SCIM and audit logs, Attestation of the model instances on request
Luminance enterprise
— · 50-seat minimum · Full proprietary AI stack, Dedicated CSM, Custom integrations · $150K–$200K+/year custom, RFP only
Confidential techIntel TDX + trust-domain GPU isolationNot offered (proprietary LLMs hosted on standard UK/EU cloud, no Intel TDX, no GPU TEE)
AttestationIntel DCAPNone
BillingPer-month subscription, cancel anytimeAnnual contract, RFP-only, custom quote, no public per-month or per-seat tier
OperatorVOLTAGE EI (France)Luminance Technologies Ltd (UK, Cambridge)
Setup~2 min, web or Telegram4–8 weeks from RFP to production (legal review, MSA negotiation, data migration)
JurisdictionFrench company, GDPR Art. 28; compute at US sub-processors (SCCs)See operator

Luminance proves you can build legal LLMs. We run open models in Intel TDX.

Most legal AI vendors are thin wrappers around OpenAI or Anthropic. Luminance is one of the few that actually built proprietary LLMs in-house, Luminance Diligence and Luminance Corporate AI are not OpenAI calls dressed up as a product. That is a real technical moat, it took a decade of work out of Cambridge, and it produces measurable benefits on legal-corpus accuracy that wrapper products cannot match. Any honest comparison page has to start there.

What that proprietary investment does not do is change where the models physically run. Luminance hosts on standard UK/EU cloud infrastructure. The models are theirs; the hypervisor underneath is not. From the workload's point of view this means Luminance the company retains technical read access to prompt content during inference, the legal contract restricts how that access is used, but the silicon does not. For most mid-market law firms working on routine contract review, that contractual posture is fine, and Luminance's model quality is the right reason to choose them.

The hardware-isolation axis is independent of the model-quality axis. A best-in-class proprietary model can run on infrastructure whose operator can read memory; an open-weight model can run inside an Intel TDX enclave whose host cannot. On VoltageGPU that enclave holds the model at our inference provider; the agent that prepares your documents runs on our servers and sees them in clear, so the isolation covers the model, not the whole path. Luminance optimises the first axis, VoltageGPU the second. The two are not interchangeable, and pretending otherwise would be dishonest.

Why hardware isolation matters more for M&A diligence than for general LLM use.

M&A diligence rooms see the most confidential corporate data inside any law-firm engagement. The full cap table sits in there. So do the term sheets, the unsigned letters of intent, the IP filings under non-public review, the employee compensation data, the customer contracts with confidentiality clauses, the unredacted financial statements, and the side-letters that the seller specifically did not want anyone outside the data room to see. The threat surface is wider than almost any other legal workflow because every category of sensitive data the firm handles ends up in the same place at the same time.

Intel TDX is one architectural answer to that threat surface. The CPU encrypts the trust domain's memory with a key it generates internally and never exposes, not to the hypervisor, not to a system administrator with root on the host. An Intel DCAP attestation quote, which a verifier can re-check offline against the Intel root certificate, shows that an instance runs as a TDX guest. On VoltageGPU this protects the model's memory at our inference provider; the documents still pass in clear through our servers on the way.

Luminance Diligence runs in the cloud regions Luminance operates and the operator (Luminance Technologies Ltd, UK) holds keys to the infrastructure. That is a contractual privacy posture, backed by SOC 2 and ISO 27001 certifications and a credible compliance team. VoltageGPU's Due Diligence Analyst agent runs on our servers (VOLTAGE EI, France, SIREN 943 808 824) and sends its model calls to an Intel TDX enclave at our inference provider; GET /v1/attestation returns the TDX quotes of the serving instances on your nonce. Our servers see the documents in clear while the agent works. Both products are credible at different regulatory tiers. The silicon path produces evidence about the model's host that the contract path does not; whether that is enough for a given diligence room is for the buyer to judge.

Where Luminance wins, and where it doesn't.

Luminance wins on proprietary LLMs purpose-built for legal corpora. Their models were trained on legal language with a specific eye to M&A diligence, contract anomaly detection, and clause-level classification, and the resulting quality on legal-domain benchmarks is a legitimate technical moat that open-weight 32B or 235B models trained on general internet text do not match for free. Luminance also wins on multi-language depth (the diligence workflow handles cross-border deals in dozens of languages with first-class quality), on the autopilot autonomous review mode released in 2023 which has had real production hours behind it, and on UK/EU operator residency without US sub-processors, a credible posture for European clients that flatly refuse US Cloud Act exposure.

Luminance loses on price transparency. The public pricing page returns a 404 as of May 2026 and every commercial conversation routes through an RFP with annual-commit terms. Public reporting clusters real deals at $3,000+ per month at the entry tier and $50K to $200K+ per year at the enterprise tier, but a buyer cannot self-serve, cannot start in one afternoon, and cannot cancel monthly. Luminance also has no hardware isolation of the model: there is no Intel TDX in their stack, no GPU TEE, no attestation chain rooted in Intel silicon. And Luminance loses on extensibility for teams that want to bring their own agents or workflows: there is no BYOA pattern equivalent to VoltageGPU's OpenClaw / CrewAI integration where a customer can ship a custom agent against the same confidential infrastructure that runs our shipped agents.

The honest framing is this. For pure M&A diligence on proprietary corporate corpora where the model accuracy is the dominant factor and the regulatory posture of contractual confidentiality is sufficient, Luminance may be the better fit and we would say so to a prospect's face. For workflows where the buyer wants the model in a hardware enclave with an attestation, where the procurement team needs transparent per-month pricing without an RFP, and where the engineering team wants to extend the platform with custom agents through OpenClaw and CrewAI, VoltageGPU is the better fit. Many firms will run both, and that is a rational outcome.

FAQ

Luminance built proprietary LLMs. Are your open-weight models behind?

Honest answer: on raw legal-domain accuracy for M&A diligence specifically, Luminance's proprietary models may lead on M&A-specific benchmarks because they were trained for that workload over a decade. We are not going to claim parity on that axis without evidence we do not have. We bet on a different axis: hardware isolation of the model plus open-weight transparency. Open weights mean anyone can audit what the model actually does, independent researchers, the customer's own security team, an EU AI Act auditor, because the parameters are public. Intel TDX means the host of the model cannot read the enclave's memory during inference; on VoltageGPU our own servers still see your documents in clear on their way to the model. The two are different optimization choices for different threat models. For a firm whose primary risk is exposure of the model's memory on the inference host rather than benchmark accuracy on M&A clauses, the open-weight TEE path is the better fit on that axis. For a firm whose primary risk is missing a non-standard clause in a complex cross-border merger, Luminance's proprietary models may legitimately be the better tool.

Does Luminance run in Intel TDX or confidential compute?

Not as of May 2026. Luminance hosts on standard UK/EU cloud regions, strong on data-residency and SOC 2 / ISO 27001 controls, but no Intel TDX, no NVIDIA GPU TEE, no trust-domain GPU passthrough, no DCAP attestation chain rooted in Intel silicon. The operator (Luminance Technologies Ltd) holds infrastructure keys and is contractually bound by the customer agreement. That is a credible privacy posture for the majority of legal workloads and is the market norm for UK/EU legal AI. It is not the same architectural class as a deployment where the model's host is constrained by hardware rather than by contract. On VoltageGPU the agents' model runs inside Intel TDX guests at our inference provider, and GET /v1/attestation returns the TDX quotes and NVIDIA GPU evidence of those instances; the agents run on our servers, which see the documents in clear. For workflows that require hardware-rooted attestation in the technical measures clause of a GDPR Article 28 DPA, the architectural difference matters; for workflows where contractual confidentiality is sufficient, both providers are appropriate.

What does Luminance's "autopilot" mode do that you don't?

Luminance Autopilot, released in 2023, is an autonomous review mode for diligence workflows, the system reads a document set, classifies clauses, flags anomalies and missing provisions, and produces a structured review without per-document human triggers. It is one of the more mature autonomous-review implementations in legal AI and has measurable production hours behind it. VoltageGPU's Due Diligence Analyst agent is in the same functional category: it ingests a document set, runs clause-level analysis, flags anomalies, and produces structured output through an OpenAI-compatible API. The functional surface is comparable and a procurement team evaluating both products would find similar capabilities on paper. The differences are architectural rather than functional. Our agent's model runs inside Intel TDX, and the TDX quotes of its serving instances can be verified against Intel's root certificate offline; Luminance's cannot. Our agent exposes an OpenAI-compatible API for programmatic access from custom code; Luminance's autopilot is primarily a web-UI workflow. Our agent can be extended with customer-written sub-agents through OpenClaw / CrewAI integration; Luminance's is a closed product surface. Pick the trade-off that matches the buyer's actual constraint.

Pricing, Luminance won't quote me. What's a real number?

Public reporting on Luminance commercial deals clusters around $3,000+ per month at the entry tier (Luminance Corporate AI, roughly $36,000 per year), $5,000 to $8,000 per month at the mid-tier (Luminance Diligence, $60K–$100K per year), and $150K to $200K+ per year at the enterprise tier with dedicated customer-success and custom integrations. All of these are RFP-only, annual-commit, and there is no public self-serve checkout. For a mid-market firm evaluating the procurement effort, that means a four-to-eight-week cycle from RFP to production including legal MSA review and data migration. VoltageGPU prices are transparent on the website and the buyer can self-serve in an afternoon. Confidential Agents Starter is $349 per month ($4,188 per year), Professional is $1,199 per month ($14,388 per year) and includes all nine vertical agents with 5,000 reviews per month, Enterprise is $3,499 per month ($41,988 per year) with unlimited reviews on DeepSeek-V3.2-TEE. No RFP, no annual commit, cancel monthly. For a firm that wants to pilot legal AI before committing to a year-long contract, the pricing model itself is the differentiator before any architectural argument starts.

Can I use Luminance for diligence and your agents for compliance?

Yes, this is a common procurement pattern and a rational one. Many firms run a diligence-specialist tool (Luminance, Kira Systems, Diligen) alongside a general-purpose AI layer for the rest of the practice. The diligence-specialist sits inside the deal room and handles M&A document review with the depth of a proprietary legal LLM. The general-purpose AI layer handles everything else, internal contract review at the partner-track level, compliance monitoring under FCA / AMF / BaFin frameworks, medical-record analysis for personal-injury or pharma work, HR-policy review, tax-document analysis, and litigation research. VoltageGPU's nine vertical agents (Sovereign Legal AI, Contract Analyst, Due Diligence, Compliance Officer, Medical Records Analyst, Tax Analyst, HR Analyst, Financial Analyst, Cybersecurity Analyst) are deliberately broad rather than M&A-specialist, they are designed to be the general-purpose layer that complements a deep diligence tool rather than to replace it. The two product categories run on different infrastructure, against different threat models, and a procurement decision that takes the best-of-breed in each category is a defensible architecture choice. The OpenAI-compatible API surface of our agents also means integration into a firm's document-management system (iManage, NetDocuments, SharePoint) is the same shape as any other LLM integration the firm already runs.

Other assistants and tools compared

Published prices beat opaque RFP pricing.

$349/mo confidential legal agents, model in Intel TDX. No RFP, cancel anytime.

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