ORVIXLABSPrivate AI systems
// SOLUTION

AI for law firms

Intake, multi-source research, document review, timelines and follow-up for law firms with traceable evidence, confidentiality and human professional authority.

CASE FILE EVIDENCE LAWYER LEGAL + IAORVIXLABS

// SOLUTION ARCHITECTURE
CONNECT WHAT ALREADY WORKS · ADD THE INTELLIGENCE THAT IS MISSING CASE FILESCONTRACTSCLIENTS EVIDENCE + AIINTEGRATE · COORDINATEAUTOMATE · TRACEwithout replacing systems that still work RESEARCHINTAKELAWYER measure → learn → adjust

// USE CASES
01New-matter intake
02Multi-source research
03Document review
04Timelines and evidence
05Client follow-up

Automate legal work without automating professional responsibility

A firm can automate matter intake, classification, document organization, follow-up and research. Legal conclusions, strategy and any advice carrying professional responsibility remain under lawyer control.

Structured and traceable intake

The system can collect background, documents, dates, parties and objectives, detect missing critical information and prepare a review summary. Matter acceptance, conflicts and scope continue to follow the firm’s professional rules.

Research and verification as separate functions

CASANDRA can expand sources, relationships and investigation paths. CERBERUS can demand evidence, detect contradictions and keep missing facts missing. Architecture prevents the same mechanism that discovers a hypothesis from certifying it.

Documents with evidence chains

A relevant claim should trace back to its document, date, fragment and version. Facts, inferences and unverifiable content remain distinct so professionals can review the path instead of trusting an opaque summary.

Confidentiality and provider boundaries

Matter files may contain health, financial, biometric, criminal-history or other sensitive data. Varexis can reduce what external models receive and separate protection from rehydration permissions where the matter requires it.

Integration with the firm’s operation

Document management, legal CRM, email, calendars and repositories can remain sources of truth. The intelligence layer reads, organizes and updates through authorized interfaces without requiring full replacement.

Quality criterion

The goal is not to produce text that merely sounds legal. It is to reduce research and organization time while preserving traceability, contrary evidence, uncertainty and identifiable professional responsibility.

// PRIVACY & COMPLIANCE

A case file can cross multiple protected data categories.

01

GDPR (European Union): minimization, purpose limitation, security and heightened protection for special-category data.

02

UK GDPR + Data Protection Act 2018: UK obligations for processing, security and special-category data.

03

Law 25.326 (Argentina): personal-data and sensitive-data protection framework.

04

LGPD (Brazil): Brazilian framework for personal and sensitive data, including health and biometric data.

OrvixLabs designs technical controls to support compliance. Actual applicability, lawful basis, contracts, consent and professional obligations depend on each organization and jurisdiction.


// FAQ

Frequently asked questions

Does AI give legal advice to the client?+

That is not the proposed function. The system can research, organize and support; professional responsibility remains with the lawyer.

Can real identities be kept away from an external provider?+

Yes, when architecture includes a data boundary such as Varexis and the matter policy requires it.

Does OrvixLabs sell one fixed product for this use case?+

No. These pages describe capabilities and architecture patterns. The final system is designed around each organization’s operations, integrations, data and limits.

Can we start with only one part?+

Yes. We prefer introducing one concrete capability, measuring it against a baseline and expanding only after value is demonstrated.

How is the final architecture defined?+

After reviewing the real process, existing systems, data, risks and available integrations. Engines are components, not the starting point.

// ORVIXLABS

The architecture is defined around the operation, its data, constraints and verification requirements.

Discuss an architecture