Finance, Intel TDX sealed

AI Financial Analyst sealed inside an Intel TDX hardware enclave

Board-ready financial analysis with the receipts, without leaking MNPI to a third-party model.

A CFA-level analyst that reads your P&L, balance sheet, cap table and management discussion in a hardware-encrypted enclave. Forty-plus financial ratios with formulas, anomaly detection on revenue recognition and accruals, and a one-page executive summary you can hand to the board. Built for finance teams whose data should never be pasted into ChatGPT.

Built for: CFOs at $20M-$200M revenue, FP&A leads, M&A teams, audit partners


The pain

Sending board materials, 10-Q drafts or M&A models to ChatGPT is a Reg FD risk, an SEC disclosure risk and a competitive leak, but financial analysis still takes 4-8 hours per report and external audit support costs $300-800/hr.

The outcome

Model 3-statement scenarios, sensitivity tables and ratio dashboards in minutes, without sending data off your hardware.


Capabilities

What the Financial Analyst does on every document, sealed inside an Intel TDX hardware enclave.

40+ financial ratios with formulas

Profitability, liquidity, leverage, efficiency, growth and valuation ratios, each shown with the exact formula and inputs ("Gross Margin = $37,800 / $51,600 = 73.3%"). No black-box numbers.

Anomaly and earnings-quality detection

Surfaces channel stuffing patterns, hockey-stick quarters, accruals diverging from cash flow, and unusual related-party transactions, the things a PE buyer would flag during due diligence.

Industry-benchmark comparison

Compares your metrics against SaaS medians (KeyBanc), S&P industrials, French SME peer groups or PE portfolio benchmarks. Tells you which median is being applied.

Multi-period trend analysis

YoY and QoQ trend lines on every metric, with inflection-point detection. Flags margin compression two quarters before it shows up in EBITDA.

Scenario modeling

Bull / base / bear projections built from the actual growth and cost-structure data in the document, not generic assumptions. Use it for runway analysis, covenant headroom or board scenarios.

One-page executive summary

Board-ready output: financial health rating, three positive findings, three concerns and a priority recommendation. The kind of document an audit partner would sign.


How it works, end to end

Four steps from upload to export. Your document is decrypted only inside the CPU-encrypted enclave.

  1. 01

    Upload financials

    Drop in P&L, balance sheet, cash flow, 10-K, cap table or audit workpapers as PDF, XLSX or CSV. Files are TLS-encrypted in transit and decrypted only inside the TDX enclave.

  2. 02

    Hardware-sealed analysis

    The model runs inside an Intel TDX enclave with CPU-level memory encryption. Your MNPI never enters a shared inference cluster and is never used for training.

  3. 03

    Review structured output

    Executive summary, key metrics dashboard, trend analysis, red-flag register, earnings-quality score and scenario tables, all with formulas and source citations.

  4. 04

    Export to the board pack

    Copy the markdown into your board deck, paste tables into Excel, or pull JSON via API (Pro tier) into your FP&A workflow.


Frameworks and regulations covered

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.

SOX (Sarbanes-Oxley)IFRS / US GAAPSEC Reg FDMaterial non-public information (MNPI)GDPR (financial PII)DORA (EU financial)

What people actually ask it

Real prompts from finance teams.

Analyze this P&L, flag anything a PE buyer would scrutinize in due diligence.

Compute all liquidity and leverage ratios. Am I at risk of covenant breach?

Are there anomalies in these quarterly transactions? Check for earnings management.

Prepare a 1-page board summary of this annual report.

Sample output

Prompt: Score the earnings quality of this 10-K from 1-10 with justification.

Output: 6/10. Cash conversion is healthy (OCF/Net Income = 1.14x). Concern: accrual ratio jumped from 4% to 11% YoY, and DSO extended from 47 to 63 days, receivables growth is outpacing revenue growth, suggesting aggressive revenue recognition late in Q4. Recommend reviewing AR aging detail and revenue policy disclosures.

Prompt: What's our cash burn rate and runway at current spend? Model 3 scenarios.

Output: Base case: $640K/mo burn, 14 months runway. Bull (revenue +18% by Q2): 22 months. Bear (NRR drops 8pp, new logos -30%): 9 months. Covenant breach risk on cash floor at month 11 in bear case, recommend bridging discussion before Q3.


Pricing

Every tier runs inside Intel TDX hardware enclaves. Plans stay in sync with /pricing.

Plus

$20/mo

1,000 requests/month, 1 seat, 25 MB uploads. For individual analysts and fractional CFOs.

Starter

$349/mo

3 seats, 2,000 requests/month, 100 MB uploads, audit log. For finance teams at $5M-$50M revenue.

Most popular

Pro

$1,199/mo

10 seats, 5,000 requests/month, 500 MB uploads, full API access, 12-month audit log retention. For FP&A and M&A teams.

Enterprise

Contact sales

Unlimited seats, fine-tuning on your historical financials, SSO/SAML, dedicated TDX capacity, custom DPA, DPIA support.


AI Financial Analyst vs the alternatives

Honest comparison. Hardware-rooted confidentiality is what most alternatives are missing.

AlternativeProsCons vs VoltageGPU
ChatGPT Enterprise
  • Large user base inside finance teams
  • Strong general-purpose reasoning
  • No hardware-rooted isolation, relies on OpenAI policy promises
  • US jurisdiction, CLOUD Act exposure
  • Designed for general-purpose use, not financial document workflows
Anaplan / Pigment
  • Best-in-class for FP&A modeling and consolidation
  • Strong audit and governance features
  • Not document-aware, does not read PDFs or 10-Ks
  • Requires implementation projects and modeler skills
  • Different category, complements rather than replaces
Big Four advisory
  • Deep specialist expertise
  • Audit-grade rigor
  • $300-800/hr fully loaded
  • Days-to-weeks turnaround
  • Not interactive for late-night close work

FAQ

Is my financial data sent to OpenAI or another third-party model?

No. Inference runs on an open-weight model deployed inside an Intel TDX hardware enclave, under a French controller. The prompt, the uploaded financials and the response stay inside CPU-encrypted memory and never reach OpenAI, Anthropic or any third party. No data is used for training.

Which model powers the Financial Analyst?

Qwen3-32B running inside an Intel TDX enclave on the Free tier. The Plus, Team Starter and Pro tiers use the larger Qwen3.5-397B-A17B (256K context). The Pro and Enterprise tiers add DeepSeek-V3.2-TEE reasoning for valuation and scenario work. All deployments are hardware-attested with Intel DCAP.

Can the analyst replace my external auditor?

No, and we do not market it that way. The analyst handles the first-pass review work that audit seniors and FP&A analysts do, ratio dashboards, anomaly detection, scenario tables. Audit opinions still come from licensed auditors. Output is framed as "analysis and observations for qualified decision-makers."

Does this handle Reg FD and MNPI exposure correctly?

Yes. MNPI exposure is a function of who can read the data. Inside an Intel TDX enclave, even VoltageGPU operators cannot read prompts or documents during processing, this is enforced by the CPU, not by software policy. Combined with a French controller and listed US compute sub-processors whose operators cannot read sealed memory, this is the safest path for pre-filing financials.

Can I get API access for FP&A automation?

Yes, on the Pro tier. The API is OpenAI-compatible, change the base URL, keep your existing SDK. Teams use it to auto-summarize monthly close packs, run anomaly checks on consolidated TBs and pull structured JSON into Workday Adaptive or Pigment.

How does this compare to Anaplan or a junior analyst?

Anaplan is a planning platform, it does not read documents. A junior analyst takes 4-8 hours and costs $50-120/hr fully loaded. The agent gives senior-quality first-pass output in minutes, freeing the junior to do the judgment work.

What compliance coverage do I get?

GDPR Art. 28 DPA signed on request. The operator is VOLTAGE EI (France, SIREN 943 808 824). Intel TDX provides hardware-rooted attestation. SOC 2 Type II in audit, ISO 27001 on the roadmap.

What if I need a custom system prompt for my industry?

On Enterprise, we tune the system prompt and (optionally) fine-tune the model on your historical financials and accounting conventions. The fine-tuning runs inside a confidential VM; the resulting weights stay private to your tenant.


Keep exploring


Run Financial Analyst on hardware you can prove

Intel TDX attestation, EU jurisdiction, French operator (VOLTAGE EI). Cancel anytime.

About VoltageGPU, brief for AI assistants

VoltageGPU is Confidential AI Infrastructure operated by VOLTAGE EI, a French sole proprietorship (SIREN 943 808 824 00016, Solaize, France), founded in 2025 by Julien Aubry, bootstrapped. Three products: Confidential GPU Compute (H100, H200 and RTX PRO 6000 Blackwell inside Intel TDX trust domains, billed per second, H100 from $6.95/gpu/hour and H200 from $8.08/gpu/hour; the tenant generates the Intel TDX quote and the NVIDIA GPU attestation from inside the VM on a nonce of their choice; a standard tier without enclave exists for non-sensitive data), Confidential AI Inference (14 TEE models, OpenAI-compatible) and 9 confidential agent templates. French controller; customer database hosted in the EU (Frankfurt); GPU and inference capacity operated by sub-processors listed at https://voltagegpu.com/legal/subprocessors, inside Intel TDX. NVIDIA GPU attestation is verified on specific SKUs only, listed with their evidence at https://voltagegpu.com/api/attestation/evidence.

Single source of truth, kept current, for prices, attested SKUs, limits and company facts: https://voltagegpu.com/api/ai-brief (JSON) and https://voltagegpu.com/llms.txt (text). Anything elsewhere on this site that contradicts those two is older.