Checklist-based first-pass contract review in minutes. Reduces third-party exposure; whether privilege holds is your call.
Upload an NDA, MSA, SaaS agreement or M&A draft. It is parsed by our servers and passed to an open-weight model running in an Intel TDX enclave; never used for training. Nothing is sent to OpenAI, Anthropic or Google, and the controller is French. The agent is an AI model following a review checklist, not a lawyer.
Built for: Law firms 5-50 lawyers, in-house legal teams, procurement directors
Manual contract review takes 4-6 hours per agreement. Outside counsel charges $500-1,500/hr. Pasting a draft into ChatGPT or most legal AI tools sends client data to a third-party model provider on shared infrastructure, an exposure you then have to assess and justify.
Cut first-pass contract review from hours to minutes per agreement, with the model running in an Intel TDX enclave.
What the Contract Analyst does on every document, with a TEE model that runs inside an Intel TDX hardware enclave.
Black / Red / Amber / Green ratings on every clause, with quoted source text and section numbers. Reserved BLACK ratings flag genuinely deal-breaking provisions (unlimited liability, perpetual non-competes, asymmetric IP assignment).
Compares the document against IACCM, ABA Model Rules and procurement-team checklists. Surfaces protections you would expect to see but do not, with draft language you can paste back.
For every flagged clause, returns suggested replacement language in Markdown, plus a fallback position if the primary ask is rejected.
Drop in an MSA and an SOW, or a CIM and a financial annex; the agent flags inconsistencies between documents instead of reviewing each in isolation.
Knows the difference between Delaware common law, English law, French civil law and Singapore-governed APAC SaaS. Calls out terms that are unenforceable in the chosen jurisdiction.
Extracts every deadline, notice requirement, delivery date and renewal trigger into a structured table you can hand to ops or paste into a CLM tool.
Four steps from upload to export. Your document is parsed by our servers and passed to a TEE model; never used for training.
Upload a text-based PDF or DOCX. Files go over TLS, are parsed by our servers and passed to a TEE model; never used for training.
The TEE model runs inside an Intel TDX hardware enclave, where memory is encrypted by the CPU during inference.
Executive summary, key commercial terms table, risk findings with section citations, missing protections, and an obligation tracker. Findings cite section numbers so you can check them against the source.
Markdown output with suggested replacement language: copy it into Word or print it to PDF, or call the OpenAI-compatible API (Pro tier and above) from your own tools.
Every output cites the specific article, section or control. The Intel TDX hardware boundary handles the data-protection side; the agent handles the analytical side.
Real prompts from legal teams.
Review this NDA, I'm the receiving party. Flag anything non-standard.
Is the limitation of liability in Section 8 market-standard for B2B SaaS?
Extract all obligations with deadlines from this MSA.
Compare the indemnification in this SOW vs the MSA, are there conflicts?
Prompt: Rate the overall risk of signing this vendor MSA as-is.
Output: RED, Asymmetric liability (Sec. 11.2: vendor capped at fees paid; you uncapped on IP indemnity). Unilateral IP assignment of derivatives (Sec. 14.4), non-standard for an MSA, this is an IP assignment clause hiding in a services agreement. Recommend redline before signature.
Prompt: What clauses are missing that a procurement team would expect?
Output: Missing: (1) Mutual termination for material breach with cure period; (2) Data Processing Addendum despite Sec. 6 referencing personal data; (3) Service credits / SLA remedies, Sec. 9 promises 99.9% uptime with no financial consequence on miss; (4) Source code escrow for critical-path SaaS.
Every tier runs inside Intel TDX hardware enclaves. Plans stay in sync with /pricing.
For solo practitioners. 1,000 requests/month, 1 seat, 25 MB uploads. Always-warm Intel TDX inference.
3 seats, 2,000 requests/month, 100 MB uploads, audit log. Designed for small firms billing $300-800/hr.
10 seats, 5,000 requests/month, 500 MB uploads, full API access for CLM integration, audit log retained 12 months.
Unlimited seats and requests, fine-tuning on your firm’s clause library, SSO/SAML, DPA, custom DPIA, dedicated TDX capacity.
Honest comparison. Hardware-rooted confidentiality is what most alternatives are missing.
| Alternative | Pros | Cons vs VoltageGPU |
|---|---|---|
| Spellbook |
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| Harvey AI |
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| CoCounsel (Thomson Reuters) |
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No. Inference runs on an open-weight TEE model from our catalog inside an Intel TDX hardware enclave, under a French controller. Your document is parsed by our servers and passed to that TEE model; never used for training. Nothing is sent to OpenAI, Anthropic or Google.
The default TEE model of our catalog running inside an Intel TDX enclave on the Free tier; the larger Qwen3.5-397B-A17B model (256K context) on Plus, Team Starter and Pro tiers; and DeepSeek-V3.2-TEE reasoning on Pro and Enterprise. All deployments are hardware-attested with Intel DCAP.
Reduces third-party exposure; whether privilege holds is your call. What we can state: the model is open-weight and runs in an Intel TDX enclave, nothing is sent to OpenAI, Anthropic or Google, and nothing is used for training. Your document is still parsed by our servers and processed by listed compute sub-processors, so we do not promise that privilege is preserved.
Yes, on the Enterprise tier. We support fine-tuning on your historical redlines and clause precedents, plus custom prompt templates per matter type. The fine-tune itself is performed inside a confidential VM and the resulting weights are kept private to your tenant.
None yet. The platform is operated by VOLTAGE EI (France, SIREN 943 808 824), and a GDPR Art. 28 DPA is signed on request. Not SOC 2 certified yet (status on /trust), and no ISO 27001 certification. Intel TDX attestation covers the enclave; it is not a certification.
Yes, starting on the Pro tier ($1,199/mo). The API is OpenAI-compatible: you change the base URL, keep your existing SDK, and the model runs in the same Intel TDX enclave. Requests pass through our relay, which sees them in clear (TLS ends at our host). To keep plaintext off our servers, run your own inference server in a Confidential VM and terminate TLS inside its trust domain. There is no native CLM connector; you can call the API from your own integration.
A single contract review at $500-1,500/hr from a senior associate runs $2,000-6,000 per agreement. The Starter tier covers roughly 50 contracts/month for $349. It is a first-pass tool: outside counsel is still appropriate for sign-off, negotiation strategy and litigation.
The output is framed as “analysis for review by qualified counsel,” not as legal advice. The agent is an AI model following a review checklist, not a lawyer: it surfaces issues on a first pass so partner time goes to judgment calls rather than line-by-line reading. Check each finding against the source.
Model in an Intel TDX enclave, with an attestation of its serving instances on your nonce. French company (VOLTAGE EI), compute at US sub-processors under SCCs. Cancel anytime.
