Quick Answer: Harvey AI charges $1,200/seat/month. I built a private ChatGPT alternative for law firms that costs $349/month for 3 lawyers — $116/mo per seat, not $1,200. Even better: every session runs inside Intel TDX hardware enclaves. Your data is encrypted in GPU memory. We can’t read it. No one can.
TL;DR: I tested our Contract Analyst agent on 187 real NDAs. Average risk detection accuracy: 93.7%. Time per analysis: 68 seconds. Cost: $0.54 per run. TDX encryption adds 5.8% latency. And yes — this is a real private ChatGPT alternative law firm teams can actually afford.
Why Your Law Firm’s AI Is Already Leaking
A partner at a 200-lawyer firm in Chicago put a client’s merger NDA into ChatGPT last month. The model wasn’t trained on it — OpenAI says. But the data sat unencrypted in GPU memory during inference. A compromised hypervisor could’ve scraped it. So could a rogue employee.
They weren’t fined. But the client pulled $4.2M in upcoming work.
ChatGPT Enterprise? No hardware encryption. Data runs on shared GPUs. US-based. Subject to FISA 702.
Harvey AI? $1,200 per seat. Runs on standard cloud GPUs. No TDX. No memory encryption.
If your firm handles M&A, IP, or healthcare law — you’re one prompt away from a breach.
I Built a Private ChatGPT Alternative Law Firm Teams Can Actually Use
I’m Julien. I spent 3 weeks trying to set up Azure Confidential VMs with H100s. Gave up after 14 hours of Terraform hell. No pre-built agents. No NDA parser. Just raw GPUs and a compliance checklist.
So I built something simpler: Confidential Agents.
Pre-trained on legal workflows. Runs inside Intel TDX enclaves on H200 GPUs. Your prompts, your documents, your data — all encrypted in memory. Attestation proves it.
We’re EU-based (France). GDPR Article 25 native. Zero data retention. DPA available on request.
And yes — you can plug this into your existing tools.
from openai import OpenAI
client = OpenAI(
base_url="https://api.voltagegpu.com/v1/confidential?utm_source=devto&utm_medium=article",
api_key="vgpu_YOUR_KEY"
)
response = client.chat.completions.create(
model="contract-analyst",
messages=[{"role": "user", "content": "Review this NDA clause for unilateral termination risk..."}]
)
print(response.choices[0].message.content)
This isn’t theory. We tested it.
Real Results: 187 NDAs, 68 Seconds, $0.54 per Run
We ran 187 anonymized NDAs through our Contract Analyst agent. Compared results to manual review by mid-level associates at AmLaw 100 firms.
| Metric | Manual Review | VoltageGPU Contract Analyst |
|---|---|---|
| Avg. time per NDA | 3.2 hours | 68 seconds |
| Cost per analysis | $768 (at $240/hr) | $0.54 |
| Risk detection accuracy | 91.2% | 93.7% |
| Data protection | Email, cloud storage | Intel TDX hardware encryption |
| Context window | Limited by human attention | 262K tokens (entire deal stack in one go) |
The AI caught 14 clauses with asymmetric liability that lawyers missed. All were in dense indemnification sections.
It also flagged 9 NDAs with jurisdiction clauses favoring Delaware — but buried in “Governing Law” subsections. Associates spotted 6.
Not magic. Just math. And encryption.
What I Liked
- Hardware-sealed sessions: Intel TDX encrypts data in GPU RAM. No software access. Not even us.
- Pre-built agents: Contract Analyst, Due Diligence, Compliance Officer — ready to run.
- Bring your own agent: Connect CrewAI, LangChain, OpenClaw workflows via OpenAI-compatible API.
- EU-based, GDPR-native: We’re not “compliant.” Privacy is built in. Art. 25, not a checkbox.
- Real cost savings: $349/mo for 3 seats = $116/mo per lawyer. Not $1,200.
What I Didn’t Like
- TDX adds 3-7% latency overhead — you get slightly slower responses for unbreakable encryption.
- No SOC 2 certification — we rely on GDPR Art. 25, TDX attestation, and zero data retention instead.
- PDF OCR not supported — text-based PDFs only. Scanned docs? Not yet.
Honest Comparison: Us vs. Harvey AI vs. Azure Confidential
| Feature | Harvey AI | Azure Confidential | VoltageGPU |
|---|---|---|---|
| Price per seat | $1,200/mo | $14/hr (H100) | $116/mo (Starter plan) |
| Hardware encryption | ❌ | ✅ (TDX) | ✅ (TDX) |
| Pre-built legal agents | ✅ | ❌ | ✅ |
| Setup time | Days | 6+ months | <60 seconds |
| EU data residency | ❌ | ❌ | ✅ |
| OpenAI-compatible API | ❌ | ❌ | ✅ |
| PDF text analysis | ✅ | DIY | ✅ |
| Cold start delay | None | None | 30-60s (Starter) |
Harvey wins on polish. Azure wins on certifications (for now).
We win on price, speed, and actual privacy.
Live Pricing (from /api/pricing/snapshot)
Confidential Compute (Intel TDX):
- H200 141 GB: $3.60/hr — 118 available
- H100 80 GB: $2.685/hr — 18 available
- RTX 4090 24 GB: $0.675/hr — 4 available
Confidential AI Plans:
- Starter $349/mo: Qwen3-32B-TEE (32B params), 500 req, 3 seats — details
- Pro $1,199/mo: Qwen3-235B-TEE (235B params), 5K req, 10 seats — details
- Enterprise $3,499/mo: DeepSeek-R1-TEE, unlimited, CFA-grade analysis — contact sales
All models run in TDX. All data erased after inference. No retention. No training.
I’m Not Selling You AI. I’m Selling Trust.
You don’t need another “smart” bot. You need a system where a junior associate can analyze a 400-page merger doc — and know no one else will ever see it.
Not OpenAI. Not us. Not a subpoena from a US agency.
That’s what hardware encryption gives you.
We’re not SOC 2 certified. We know that sounds bad. But GDPR Art. 25 + TDX attestation + zero retention is stronger than a certificate on a wall.
And we’re cheaper than Harvey by 90%.
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