Legal Intelligence
Reconstruct complete context across matter files, client history, and regulatory updates so AI can draft, research, and respond with citation-level proof.
What this breaks in the business
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Incorrect Pricing Missed technical constraints lead to margin loss.
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Lost Tenders & Delayed Incomplete compliance context slows approval
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Engineering Rework Outdated specifications trigger avoidable redesign
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Slower Sales Cycles Manual verification creates friction and drag
Nand AI Approach
Reconstructing the Legal Digital Thread
Nand AI doesn’t retrieve text. It rebuilds meaning.
Our Context Engine connects your people, your systems, and your history into a unified system of record for your firm’s collective intelligence.
- Tracks how clauses and strategies evolve across years of contracts
- Identifies who authored each precedent and why it worked
- Links regulatory changes to live proposals and templates
- Maps matter timelines across emails, documents, and case files
This is the legal digital thread rebuilt as living context.
What this enables
Gold-Standard Intelligence
Always surface the most current, approved version of clauses, strategies, and playbooks.
Provenance and Accountability
Every insight identifies the original author, matter, and approval history.
Regulatory & System Dependency Awareness
Understand how an external change impacts internal templates, RFPs, and client commitments.
OneSearch for Legal Teams
OneSearch gives business development and legal teams a single, permission-aware knowledge layer. It doesn’t return links. It delivers grounded answers.
KEY CAPABILITIES
- Direct Answers, Not Just Links
Ask: “What was our winning argument for the Client X jurisdictional challenge?” and get a synthesized response. - Permission-Aware by Design
If a user should not see a partner-level file, it never appears. - Always Current
When a document is updated or a matter closes, OneSearch reflects it immediately.
Commercial to Operational
Agentic Workflows in Action
The power of an agent is only as good as its data. By using Nand AI as your central Context Engine, you can deploy agents that execute high-stakes, multi-step workflows.
Agent 1
RFP & Proposal Agent
Deconstructs complex client questionnaires and drafts firm-specific responses using verified wins and partner bios.
Primary outcome: 50% revenue increase through faster, higher-quality bids.
Agent 2
Red Flag & Contract Agent
Analyzes incoming agreements against firm-approved Gold Standards to highlight risky deviations.
Primary outcome: 70% faster intake and consistent risk mitigation.
Agent 3
Chronological Timeline Agent
Reconstructs a complete case narrative by linking events across emails, files, invoices, and logs.
Primary outcome: Reduced discovery hours and faster trial preparation.
Agent 4
Regulatory Drift Agent
Monitors external case updates and flags internal templates or proposals that require changes.
Primary outcome: Proactive compliance and reduced client risk.
Agent 5
Supplier Agreement Analyst
Scans vendor contracts to identify expiring terms, pricing risks, and policy violations.
Primary outcome: Lower operational costs and stronger negotiation leverage.
Security & Compliance
Enterprise Security by Design
Security is not an afterthought. Our platform is built for the most stringent regulatory environments, ensuring your data never leaves your perimeter and access is strictly audited.
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Tenant-Isolated Architecture
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Zero-Training Guarantee
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(our models don't train on customer data)
Help Center
Frequently asked questions
Quick answers to questions you may have. Can't find what you're looking for? Reach us out
Magus is the execution layer powered by the Nand AI Context Engine. It securely connects to your trusted enterprise systems such as Google Drive, Salesforce, Slack, and ServiceNow, reconstructs full context across documents, authors, and timelines, and generates accurate, evidence-backed responses for workflows like RFPs, security questionnaires, and real-time sales support.
Magus is built for enterprise sales, pre-sales, proposal, legal, and procurement teams operating in complex, high-stakes environments. It is used by teams that require accurate, traceable answers across large and evolving knowledge bases. The Universal Search capability can be used across the organization to retrieve precise, context-aware answers.
Most customers are production-ready in hours, not weeks. Initial deployment is typically completed the same day, depending on the number of systems being connected.
General-purpose AI is designed for broad knowledge and open-ended conversation. It is not built for enterprise accuracy, governance, or traceability.
Magus is different in three critical ways:
- It operates only on your verified enterprise data
- Every answer is grounded with source citations
- Each response is confidence-scored to surface uncertainty
This makes Magus suitable for high-stakes enterprise workflows where correctness matters.
Accuracy is enforced through the Nand AI Context Engine and validation layer.
Every response is:
- derived from your verified source material
- checked against the knowledge graph for consistency
- rejected if it cannot be traced to a specific source or timestamp
This eliminates black-box behavior and ensures outputs are auditable.
Security is foundational to the Nand AI platform.
- All data is encrypted in transit and at rest
- Customer data is tenant-isolated
- Your data is never used to train third-party models
- Full audit trails are maintained for all access and activity
Nand AI is built for enterprise-grade security and compliance from the ground up.
Magus integrates with the systems where your enterprise knowledge already lives, including:
Google Drive, Salesforce, ServiceNow, Microsoft Teams, HubSpot, OneDrive, Jira, Zendesk, Slack, Notion, Confluence, and custom enterprise systems.
New connectors can be added without disrupting existing workflows.
Ready to build AI your partners can trust?
The next generation of legal AI won’t be built on prompts and patches. It will be built on context.