Private AI document intelligence that searches 50,000 contracts, depositions, and case files instantly — with no cloud, no data egress, and no Relativity invoice at the end of the month.
Relativity costs $50,000–$200,000 per year. Kira Systems isn't far behind. Both process your privileged documents on shared multi-tenant cloud infrastructure. Your clients never agreed to that.
$50k–$200k/yr licensing. Documents uploaded to vendor servers. Privileged material processed on shared infrastructure. Associate hours billed to review what a query could answer in seconds. Renewal negotiations every 12 months.
$6,000–$9,000 one-time setup. Flat monthly hosting. Your documents run on hardware you control — on-premise or your private cloud. Zero egress. Attorney-client privilege preserved. No per-user seats. No renewal leverage.
"Find all contracts with auto-renewal clauses and less than 60 days notice." That's a half-day of associate time. With RusticAgentic, it's a 10-second query. At $400/hr associate billing, the system pays for itself in the first week.
Natural language queries against your entire document corpus. Every answer includes the source document and paragraph. Privileged data stays privileged. Your clients get faster results. Your firm keeps the margin.
| Vendor | Annual Cost | Data Sovereignty | Natural Language Search | No Per-Seat Fees | Setup Time |
|---|---|---|---|---|---|
| Relativity | $50k–$200k/yr | ✗ Cloud | Limited | ✗ | Months |
| Kira Systems | $30k–$100k/yr | ✗ Cloud | ✓ | ✗ | Weeks |
| Luminance | $20k–$80k/yr | ✗ Cloud | ✓ | ✗ | Weeks |
| OpenAI / Claude API | $5k–$25k/yr + egress risk | ✗ OpenAI servers | ✓ | ✓ | Weeks |
| RusticAgentic | $18k–$42k/yr (all-in) | ✓ Your infrastructure | ✓ | ✓ | 72 hours |
* All-in annual cost includes setup amortized over 3 years + monthly hosting. Competitor figures from published pricing pages and industry surveys.
No training. No fine-tuning. No IT project. Your documents are chunked, embedded, and stored in a private vector index on your hardware. Queries run locally against a 12B parameter language model. Nothing touches the internet.
PDF, DOCX, scanned images. Drop into a watched folder or GCS bucket. Three-tier extraction: native text → poppler → OCR.
The ra-watch daemon detects new files within seconds. Legal-aware chunker splits at section boundaries — not arbitrary character counts.
1024-dimension embeddings computed on-device by gte-large-en-v1.5 via ONNX Runtime with CUDA acceleration. Zero API calls.
Vectors stored in a bare-metal HNSW index (usearch). Sub-millisecond approximate nearest-neighbor retrieval at any scale.
Natural language query → top-K retrieved chunks → Mistral 12B generates a cited answer. Every response shows the source document and paragraph.
"Find all MSAs with automatic renewal clauses and less than 60 days notice." Searches thousands of contracts in seconds. Returns the clause, the document, and the page number.
"Which contracts are not governed by Delaware law?" Cross-reference governing law clauses across your entire portfolio instantly. Essential for M&A due diligence.
"List all vendor agreements with liability caps below $500,000." Extracts, normalizes, and ranks contracts by exposure. No spreadsheet, no associate review hours.
Search deposition transcripts for specific testimony, contradictions, or witness statements. Cite the exact page and line. Works across hundreds of depositions simultaneously.
Rapid first-pass review of discovery productions. Identify responsive documents, flag privilege issues, and surface key facts before associate review begins.
Attorney-client privileged documents stay on hardware you control. No vendor has access. No multi-tenant server processes your matter. Provably sovereign by design.
The following output was generated by Mistral NeMo 12B running on a local GPU against a 300-document legal corpus: 80 NDAs, 50 MSAs, 40 employment agreements, 30 deposition transcripts, 25 settlement agreements, 20 board minutes, 15 IP assignments, 15 engagement letters, 10 demand letters, 10 court filings, and 5 privilege logs. Every answer is real. Every citation is real. No internet connection. No API calls.
All output generated by Mistral NeMo 12B running on a local NVIDIA GPU — zero internet connection, zero API calls, zero data egress. 300-document corpus: NDAs, MSAs, employment agreements, depositions, settlements, board minutes, IP assignments, demand letters, court filings, privilege logs.
The 8 queries you just read were generated on an NVIDIA RTX 3060 — a consumer gaming card with 12GB of memory. That is the development environment. Client deployments run on data center hardware that removes every constraint you saw: larger context windows, faster responses, more capable models, and the ability to handle your entire firm's document library simultaneously.
| Capability | Demo (RTX 3060) | GCP A100 80GB Standard Deployment |
GCP H100 80GB Premium / On-Premise |
|---|---|---|---|
| GPU VRAM | 12 GB | 80 GB | 80 GB (NVLink: 160 GB dual) |
| Language Model | Mistral NeMo 12B (quantized) | Mistral Large 2 · 123B params Full precision — significantly stronger legal reasoning |
Llama 3.3 70B or Mistral Large 2 Full precision + faster throughput |
| Context Window How much of your vault fits in one query |
8,192 tokens ~32,000 chars · ~25 pages |
128,000 tokens ~512,000 chars · ~400 pages per query — 16× the demo |
128,000 tokens ~512,000 chars · ~400 pages per query |
| Query Latency Time from question to full cited answer |
8 – 20 seconds | 2 – 5 seconds | 1 – 3 seconds |
| Inference Speed | ~25 tokens/sec | ~80 tokens/sec | ~150 tokens/sec |
| Concurrent Users | 1 (dev/demo) | 6 – 8 simultaneous attorneys | 10 – 15 simultaneous |
| Document Vault Capacity | ~50,000 docs tested | 500,000+ documents Scales with NVMe storage — no hard limit |
Unlimited Add NVMe capacity as corpus grows |
| Documents per Single Query With keyword prefilter + full context |
4 – 8 docs in context | 50 – 80 full documents in context Entire contract portfolios fit in a single query |
50 – 80 full documents in context |
| OCR for Scanned PDFs | ✓ tesseract (CPU) | ✓ tesseract + GPU-accelerated rendering | ✓ tesseract + GPU-accelerated rendering |
| Embedding Model | gte-large-en-v1.5 · 1024-dim · CUDA | gte-large-en-v1.5 · 1024-dim · A100 CUDA | gte-large-en-v1.5 · 1024-dim · H100 CUDA |
| PQ Signing | ML-DSA-65 on every output | ML-DSA-65 · full audit log encrypted at rest | ML-DSA-65 · full audit log encrypted at rest |
| Uptime | Dev machine | GCP SLA: 99.9% | GCP SLA: 99.9% / On-premise: managed |
GCP A100/H100 pricing: ~$2.50–$3.50/hr on 1-year committed use, billed to your GCP account. Estimated annual infrastructure cost: $22,000–$31,000/yr — a fraction of a Relativity license. We manage the stack; you own the machine.
Every engagement starts with a free 30-minute scoping call. We tell you exactly what we will build, what it will cost, and what you will get. No RFP process, no procurement committee, no six-month implementation timeline.
All fees are USD. Setup fees are due 50% at engagement start, 50% on go-live. Monthly retainers billed in advance. No long-term contract required on Cloud Sovereign tier — cancel with 30 days notice.
Tell us how many documents you have and what questions matter. We'll tell you exactly what we can deliver and what it will cost. First call is always free.
Or email directly: scott@duckdatamaster.guru