Research & Insights
Research that scales. Insights grounded in evidence.
Stop hunting for data and start synthesizing intelligence. Nand AI reconstructs institutional memory across your internal research, market signals, and legacy data to power deep analysis with 95% accuracy.
Problem & Impact
The Analyst’s Burden: The Research Tax
Modern researchers spend up to 70% of their day on data plumbing, leaving only 30% for strategy.
- Critical insights are trapped in call transcripts, Slack threads, PDFs, and disconnected spreadsheets
- Expertise disappears when analysts leave, forcing teams to re-research the same questions
- Search becomes “search and rescue” across siloed systems
- Generic AI summarizes, but cannot provide evidence
In high-stakes research, a claim without a verifiable citation is a liability.
Nand AI Workflow
From Raw Data to Grounded Thesis
Nand AI becomes your Foundational Context Layer.
We don’t just find files. We reconstruct the narrative behind them.
- Ingest & Unify
Securely connect internal research (memos, emails, Slack) with market signals and technical documentation. - Map Relationships
Identify how a prior patent relates to a current supply chain disruption, even across disconnected systems. - Synthesize with Provenance
Generate deep-dive briefings automatically cited to the original author, timestamp, and source.
What this enables
Institutional Memory at Scale
Preserve context beyond individual analysts and teams.
Evidence-Backed Strategy
Every insight is traceable, reviewable, and defensible.
Faster Time to Conviction
Move from data to decision without manual verification cycles.
Deep Research Synthesis
Go beyond keywords. Query meaning.
Nand AI’s Deep Research capability transforms fragmented inputs into decision-grade intelligence.
KEY CAPABILITIES
- Thesis Comparison
Compare current market signals against historical Gold Standard research to detect Alpha or Market Drift. - Cross-System Investigation
Ask: Who in our firm has experience with this regulatory clause?
Get answers grounded in actual work-product history. - Deterministic Verification
Every claim is anchored. If a source cannot be verified, it is flagged as Unverified rather than guessed.
Agentic Workflows
For the Seasoned Analyst
Deploy specialized agents to handle synthesis and monitoring with 95% answer accuracy, governed by your firm’s research methodology.
Agent 1
Market-Fit & Thesis Agent
Automatically scan new deal flow or news against internal “Success & Failure” archives to flag deviations from your core thesis.
Primary Outcome: Move faster on opportunities that align with historical winners
Agent 2
Competitive Intelligence Agent
Monitor competitor filings, news, and technical specs to generate weekly “Delta Reports” on market movement.
Primary Outcome: Identify threats and opportunities before they become public consensus.
Agent 3
Synthesis & Briefing Agent
Convert hundreds of pages of raw transcripts, notes, and emails into a structured 1-page Investment Committee or Executive briefing.
Primary Outcome: 80% faster reporting turning weeks of synthesis into minutes of review.
Agent 4
Regulatory & Trend Monitor
Track shifting regulations in Legal or Industrial Tech and map them directly to your current portfolio or product roadmap.
Primary Outcome: Proactively manage compliance changes before they impact the bottom line.
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 scale your firm’s intelligence?
The next generation of research won’t be built on better prompts.
It will be built on deeper context.