Find everything their lawyer tried to bury
CloseVector is a local, attorney-controlled evidence engine for data-heavy litigation. It helps your team surface supporting evidence, bad facts, key witnesses, timelines, privilege candidates, and citation-gated case insights while keeping sensitive matter content on firm-controlled infrastructure.
Local or air-gapped · Attorney-supervised · Citation-gated · Audit logged · Privilege-aware
- Discovery
- Hashing
- Extraction
- Normalization
- Privilege
- Indexing
- Timeline
- Contradiction
- Evidence
Illustrative synthetic matter · not live telemetry · not measured processing performance
AI Adoption Is Expected. Governance Infrastructure Is Not.
Corporate legal departments now expect outside counsel to use AI. At the same time, the majority of corporate legal professionals report they do not know whether their outside counsel are using AI on their matters, or how. The tools most firms have adopted generally do not document their search methodology, do not demonstrate completeness, and do not ensure that client data stays within the firm's control.
That gap between adoption and governance is where liability lives. It is also where CloseVector operates.
The question is no longer whether your firm uses AI. It is whether your firm can demonstrate control, auditability, and data sovereignty when a client, malpractice carrier, or regulator asks how your AI works.
Two Layers. One System.
Every search produces results and a defensible record of methodology.
Search by Meaning
CloseVector indexes the concepts in your documents, not just keywords. Search across briefs, memos, contracts, correspondence, and discovery productions using natural language. Surface relevant documents even when they use different terminology than your query.
Semantic search is where CloseVector starts, not where it stops. Within a year, a dozen tools will offer basic concept search. The verification layer is what most tools lack.
Verify with Audit Trails
Every search produces a complete, documented record: what was queried, what was retrieved, how results were ranked, what was excluded, and why. Cryptographic document hashing verifies file integrity at the time of indexing. Document relationship mapping surfaces connections between related files.
When a judge, malpractice carrier, or opposing counsel asks about your search methodology, you have a documented answer.
latency_shift → {records:[EVID-018420, EVID-018613], event:D+10, hash:7d8f06b4, run:SYN-QLCA-073}Illustrative synthetic matter · signals identify review windows · interpretation remains with the professional
One matter. A traceable path from source to challenge.
CloseVector is the platform and e-discovery is the primary workflow. QLCA: Quantitative Legal Communications Analytics operates inside that workflow before downstream adversarial analysis and the validation and provenance proof layer.
Illustrative synthetic matter · branches expand review candidates · attorney judgment controls conclusions
Three Steps to a Local Evidence Engine
Deploy On-Site
A CloseVector engineer delivers and configures the system at your office. NDA signed before any engagement. All processing runs on your hardware.
Index Locally
Your entire document corpus is indexed on local hardware. Every file is hashed for integrity verification. Documents are processed and stored entirely on your hardware.
Search & Verify
Multi-stage retrieval pipeline finds what matters. Complete audit logs document every query, retrieval, and ranking decision for your records.
Hardware You Own. Not a Subscription.
A professionally configured AI system that sits in your office and runs your entire document intelligence pipeline. Not a cloud login. Not SaaS. A tangible business asset on your balance sheet.
Physical one-way channel. Updates flow in. In air-gapped deployments there is no routine outbound network path for matter content.
For maximum security, fully disconnected with manual update delivery.
Everyone in the firm can search. No caps, no usage charges.
Local API designed for future AI agent integration with verified retrieval.
Actual configuration may vary by deployment.
Primary-Source Research
Original analysis of the legal, technical, and economic forces reshaping how law firms handle AI, data, and risk.
The Designated Defendant
How current AI deployment architectures concentrate liability on law firms, and why the Harvard JOLT framework matters for your risk posture.
Cloud AI Sovereignty & Legal Risk
A data-driven audit of cross-border data exposure, jurisdictional risk, and the structural vulnerabilities of cloud-based legal AI.
The Legal AI Billing Gap
Where AI-driven efficiency creates margin pressure for law firms, and the economic case for infrastructure ownership over subscription.
See It on Your Documents
One-week evaluation deployment. A CloseVector engineer installs the system at your office, indexes your document library, and your team uses it for a week. Search, review audit trails, and see document relationships on your actual data.
What you need
A decision-maker attends kickoff and end-of-week review. Your documents are in a local digital repository (file server, NAS, SharePoint export, or similar).
How it works
Setup fee covers hardware, travel, and on-site deployment time. Fee is credited toward full deployment if you proceed. If you do not proceed, the engineer deletes everything on-site or you keep the embeddings at cost.
Confidentiality backed by NDA and architecture. A CloseVector engineer signs an NDA before any engagement. All indexing runs locally on your hardware. You control physical access and permissions at all times. CloseVector does not copy or retain your documents.
Firms That Need Control
Firms where technology decisions can be made without a committee
Practices handling sensitive client matters where data sovereignty is non-negotiable