Confidential AI for research and legal teams
VirexaLLM runs open-weight models locally on the attorney's or researcher's own hardware — with pinnable versions, signed audit logs, and full air-gap support. Privilege and reproducibility, enforced by the architecture.
Research moves forward without leaving the perimeter
100%
On-Device
Discovery material never leaves the workstation
Air-Gap
Supported
Run inference on machines with no network at all
Pinnable
Model Versions
Lock research to a specific open-weight revision
Signed
Audit Trail
Tamper-evident logs of every query and model load
Privilege, pinning, and provenance
Everything you need to use AI on sensitive material without exposing it.
Privileged, On-Device Inference
Contracts, filings, privileged memos, and discovery material stay on the attorney's hardware. No third-party processor to add to your engagement letter.
Attorney-Client Friendly
No vendor inspecting prompts. No training on your queries — because there's no backend to train. Confidentiality is a property of the architecture, not a checkbox.
Reproducible Research
Pin a research workflow to an exact open-weight model revision. Re-run the same query against the same weights six months later and get the same answer.
Pinned Model Versions
Open-weight models don't silently change. Freeze a model at a specific GGUF hash for regulated research, citations, and expert reports.
Signed Local Audit Trail
Every query, every model load, every policy change recorded in a tamper-evident log on the device — export to your matter management system without exposing prompt content.
Dataset Replay
Replay a historical query set against any new open-weight model with one command. Compare research outputs across model generations, reproducibly.
Work teams run on VirexaLLM
Reproducible, confidential, and fully on-device.
One device, every confidential query
Load Llama 3, Mistral, Qwen, or DeepSeek directly on the researcher's machine. Every question about a privileged memo, a draft brief, or a confidential dataset gets answered by a model that never phones home.
Reproducibility, enforced by hashes
Open-weight models don't silently update. Pin a matter or a study to a specific GGUF hash and quantization. Six months later, the same query against the same weights produces the same answer — the foundation of defensible research.
Research that survives peer review
Every run captured, tagged, and replayable — including years from now.
Signed Local Traces
Every query stores prompt hash, model hash, parameters, and timestamp — exportable without revealing content.
Dataset Replay
Re-run a historical query set against any open-weight model. Keep comparisons honest and reproducible.
Version Pinning
Hold a matter or study on an exact model revision for the life of the engagement.
Security built for privileged material
Local inference, zero telemetry, signed audit logs, and air-gap support.
Frequently asked questions
Does any document content leave the device?
How does this fit attorney-client privilege?
Can we pin a model for a matter that takes years?
Is the audit trail defensible?
Can researchers reproduce experiments?
Your laptop is the server now
Download VirexaLLM and run Llama, Mistral, Phi-3, Gemma, or Qwen locally in minutes. Free desktop app for macOS, Windows, and Linux — your prompts never leave the device.