Nand AI
Nand AI is a San Francisco-based B2B SaaS company that builds a Deterministic Context Engine and Magus platform, using graph-first architecture with pre- and post-LLM validation to deliver accurate, traceable enterprise AI answers and workflow agents.
- Company typePrivate
- Founded2023
- HeadquartersSan Francisco, United States
- Headcount11–50
- GTM typeB2B
- OfferingSoftware
What Nand AI does
Nand AI is a San Francisco-based B2B SaaS company that builds a Deterministic Context Engine for enterprise AI, founded in 2023 by Shiraz Zaman (CEO, ex-Microsoft Bing Ads, ex-Lyft AI), Martin Liu (Architect), and Ammar Haris (CTO). The core Magus platform is an execution layer that ingests documents, chats, tickets, emails, and enterprise systems, then reconstructs them into a continuously evolving Enterprise Knowledge Graph that preserves authorship, section hierarchy, versions, timelines, and cross-system relationships. Two proprietary validation layers — a Context Relevance Model that filters content before the LLM and a Response Relevance Model that checks the output after generation — are positioned to reduce hallucinations and produce evidence-backed answers with full provenance. The platform supports 50+ native integrations (Salesforce, ServiceNow, Google Drive, SharePoint, Slack, Teams, Confluence, Jira, Zendesk, Notion, OneDrive, HubSpot) with inherited permissions, and is SOC 2 Type 2 certified with a zero-training guarantee and tenant-isolated architecture.
The product surface comprises the Magus platform, the OneSearch unified enterprise search product (launched October 2025), and a catalog of vertical-specific agents. Sales-and-revenue agents (CPQ, RFP, DDQ & Security) serve proposal and compliance workflows; financial-intelligence agents (Market-Fit Analyst, DDQ & Due Diligence, Portfolio Compliance, Investment Research, Internal Knowledge & Onboarding, Risk & Governance) target investment teams; and industrial/manufacturing agents (Proposal, Security & Compliance, Supply Chain Resilience, Predictive Maintenance Orchestrator, Adaptive Quality Control, Autonomous Sourcing) target industrial customers. Published pricing is tiered at $299/year (Standard), $499/year (Professional), and $999/year (Enterprise), with custom pricing for large deployments and a free self-serve signup. GTM combines enterprise field sales (Request Demo, pilot programs with direct engineering access) with a product-led self-serve motion, targeting B2B organizations of more than 100 employees with complex sales cycles and distributed knowledge. Nand AI had raised $1,000,000 in seed funding from Sequoia Scout (February 2024) as of the disclosed data, with named customers including Microsoft, Tyfone, Revine Tech, and Dickinson Wright.
Nand AI firmographics
Firmographics- Name
- Nand AI
- Legal name
- Nand.AI
- Website
- https://nand.ai
- Company type
- Private
- Founded year
- 2023
- Operating status
- Operating
- Headcount range
- 11–50 employees
- Short description
- Nand AI is a San Francisco-based B2B SaaS company that builds a Deterministic Context Engine and Magus platform, using graph-first architecture with pre- and post-LLM validation to deliver accurate, traceable enterprise AI answers and workflow agents.
- Ownership category
- akta.pro rank
Nand AI industry classification
Industry- Product category
- Enterprise AI Platform
- NAICS
- Software Publishers (5132)
- SIC
- Services-Prepackaged Software (7372)
- akta.pro primary industry
- Enterprise AI Data & Knowledge Platforms (Vector Databases, Knowledge Graphs) (HDAEANAH)
- akta.pro secondary industries
- LLM/GenAI Guardrails & Safety Controls (policy, filtering, routing) (HDAAAKAD), AI Observability, Monitoring & Evaluation Platforms (Drift, Quality, Safety) (HDAEANAF)
Keywords
Where Nand AI is headquartered
LocationHeadquarters
- HQ city
- San Francisco
- HQ country
- United States
- HQ region
- North America
Offices1 record
Markets served
Nand AI business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Marketing or Sales, Infrastructure
Revenue model
- SaaS Subscription (Magus Platform): Subscription-based B2B SaaS platform with tiered pricing plans (Standard, Professional, Enterprise). Access to automated processing for Enterprise Search, DDQs, RFPs, and CPQs, AI-powered document analysis and knowledge management, enterprise search and conversational AI capabilities.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Subscription | Annual | Standard - For individuals and small teams |
| Subscription | Annual | Professional - For individual account executives |
| Subscription | Annual | Enterprise - For medium and large sales organizations |
Go-to-market motion2 records
Distribution channels3 records
Marketing channels3 records
Nand AI product offering
Product offeringCore offering
Nand AI builds and sells a Deterministic Context Engine for enterprise AI, delivered through its Magus execution-layer platform. The platform reconstructs enterprise knowledge as a continuously evolving knowledge graph that preserves authorship, hierarchy, versions, timelines, and cross-system relationships, then powers unified search (OneSearch) and specialized AI agents for sales, compliance, financial, and industrial workflows. Customers subscribe to Magus on tiered annual SaaS plans and deploy agents such as CPQ, RFP, DDQ, Market-Fit Analyst, Due Diligence, Portfolio Compliance, Proposal, and Supply Chain Resilience.
Product overview
Nand AI offers a platform-plus-modules architecture centered on its Deterministic Context Engine. The core Magus platform is the execution layer powered by the Context Engine, which reconstructs complete meaning across enterprise data by building a living knowledge graph. Built on Magus, OneSearch provides unified enterprise search that synthesizes verified answers rather than returning links. Multiple specialized AI agents extend the platform: CPQ Agent, RFP Agent, and DDQ & Security Agent handle enterprise sales and compliance workflows; financial-specific agents (Market-Fit Analyst, DDQ & Due Diligence, Portfolio Compliance, Investment Research, Internal Knowledge & Onboarding, Risk & Governance Intelligence) serve investment teams; and industrial agents (Proposal, Security & Compliance, Supply Chain Resilience, Predictive Maintenance, Adaptive Quality Control, Autonomous Sourcing) serve manufacturing and supply chain operations. The platform achieves 90% recall and 95% accuracy through its graph-first architecture with pre- and post-LLM validation layers.
Differentiator
Problem solved
Functional benefit
Brands
- Magus: The execution layer powered by the Nand AI Context Engine that delivers accurate answers, agents, and automation across enterprise workflows.
- OneSearch
Products and services
- Magus Core execution-layer SaaS platform powered by the Nand AI Context Engine that delivers accurate answers, AI agents, and automation across enterprise workflows. Magus securely connects to enterprise systems and reconstructs full context across documents, authors, and timelines to generate evidence-backed responses.
- OneSearch Unified enterprise search product that reconstructs full context across documents, chats, tickets, and systems and synthesizes a single evidence-backed answer. Reports 6x better recall, approximately 40 percentage points better accuracy, and approximately 50 percentage points better comprehensiveness versus traditional search.
- CPQ Agent Precision engine for quote-to-cash workflows that interprets requirements, applies pricing logic, and generates approval-ready quotes with built-in margin validation and complex pricing guardrails. Targeted at enterprise sales and revenue operations teams.
- RFP Agent Intelligent document system that deconstructs questionnaires, retrieves validated answers from the enterprise knowledge base, and drafts structured responses with knowledge reuse and review flagging for low-confidence areas. Targeted at pre-sales and bid management teams.
- DDQ & Security Agent Compliance control center that responds to security and compliance questionnaires (SOC 2, ISO, GDPR) with answers grounded in verified policies, full audit trails, and clickable citation chains.
- Market-Fit Analyst Agent Automates early-stage investment screening by cross-referencing new deal flow against historical success and failure archives and flagging deviations from core investment criteria. Targeted at financial services and investment teams.
- DDQ & Due Diligence Agent Accelerates investment diligence by parsing DDQs, data rooms, and disclosures and flagging red risks based on historical deal outcomes.
- Portfolio Compliance Agent Monitors internal communications for governance risk with contextual understanding, tracking MNPI references and mapping activity to internal compliance policies.
- Investment Research Assistant Agent Supports deep investment research by connecting analyst notes, market research, and internal commentary to produce grounded summaries with full provenance.
- Internal Knowledge & Onboarding Agent Preserves and scales institutional knowledge inside investment firms by answering questions on internal processes, tools, and best practices grounded in approved firm documentation.
- Risk & Governance Intelligence Agent Surfaces hidden exposure across investment activity by connecting deal activity to internal risk thresholds and flagging inconsistencies across approvals and execution.
- Proposal Agent Automates complex technical proposals for industrial and manufacturing buyers by matching buyer-added conditions against live engineering specifications and BOMs and validating technical feasibility before submission.
- Industrial Security & Compliance Agent Answers ISO, NIST, SOC 2, and customer security questionnaires with audit-ready accuracy for industrial and manufacturing organizations by pulling evidence from internal audits, policies, and control documents.
- Supply Chain Resilience Agent Anticipates supply chain disruptions for industrial operations by monitoring supplier performance, logistics signals, and external risk factors and connecting external events to internal inventory and production timelines.
- Predictive Maintenance Orchestrator Prevents industrial downtime by analyzing IoT logs, service manuals, and historical maintenance records to predict failure windows and automatically schedule service and order parts.
- Adaptive Quality Control Agent Finds manufacturing defects and traces root cause across the production chain by linking vision data, shift logs, and supplier batches to identify systemic quality issues.
- Autonomous Sourcing Agent Manages RFQs and supplier selection for industrial buyers using real demand context, issuing RFQs based on live production requirements and comparing suppliers using performance history and contract terms.
Quantifiable outcome
- 6x better recall than traditional retrieval-based search
- +5 more outcomes
Companies that use Nand AI
Customer profileNamed customers5 records
Segments4 records
Ideal customer profiles4 records
Nand AI technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- No
- API docs
- API detail
Core technology
AI maturity
App detail
Integration12 records
AI capability5 records
Feature7 records
Nand AI partnerships and signals
Strategic signalPartnerships
15 partnerships are on record, tiered core.
- GooglecoreGoogle appears as a trusted customer logo and integration partner. Nand AI integrates with Google Drive and OneDrive for enterprise data connectivity.
- MicrosoftcoreMicrosoft appears as a trusted customer logo and integration partner. Integration with Microsoft Teams, SharePoint, and OneDrive. Testimonial from Hiren Patel, Principal Product Manager at Microsoft.
- LinkedIncoreLinkedIn appears as a trusted customer logo on the Nand AI website.
- Lockheed MartincoreLockheed Martin appears as a trusted customer logo. Advisor Craig Martell is CTO of Lockheed Martin, providing strategic guidance.
- Google DrivecoreIntegration with Google Drive for secure document connectivity. Part of 50+ enterprise data source integrations.
- SalesforcecoreIntegration with Salesforce for CRM connectivity. Part of 50+ enterprise data source integrations supporting deal context and customer intelligence.
- ServiceNowcoreIntegration with ServiceNow for enterprise ticketing and workflow systems. Part of 50+ enterprise data source integrations.
- SlackcoreIntegration with Slack for collaboration and communication data. Part of 50+ enterprise data source integrations.
- Microsoft TeamscoreIntegration with Microsoft Teams for enterprise collaboration. Part of 50+ enterprise data source integrations.
- HubSpotcoreIntegration with HubSpot for CRM and marketing automation. Part of 50+ enterprise data source integrations.
- ConfluencecoreIntegration with Confluence for enterprise wiki and documentation. Part of 50+ enterprise data source integrations.
- JiracoreIntegration with Jira for project tracking and issue management. Part of 50+ enterprise data source integrations.
- ZendeskcoreIntegration with Zendesk for customer support ticketing. Part of 50+ enterprise data source integrations.
- NotioncoreIntegration with Notion for documentation and knowledge management. Part of 50+ enterprise data source integrations.
- OneDrivecoreIntegration with OneDrive for Microsoft document storage. Part of 50+ enterprise data source integrations.
Scale indicators11 records
Recent moves6 records
Expansion highlights5 records
Nand AI competitors and assessment
Company assessmentDirect peers
- Glean Technologies: Glean is the most direct competitor in enterprise AI-powered search and knowledge management. Both companies index across SaaS apps (Salesforce, Slack, ServiceNow, etc.), use retrieval architectures to surface answers, and target enterprise B2B buyers with PLG-to-enterprise motions.
- Hebbia: Hebbia focuses on AI agents for knowledge work in financial services and professional services, with a similar emphasis on document-grounded answers and audit trails. Competes with Nand AI's financial intelligence agent suite (Market-Fit Analyst, DDQ & Due Diligence, Portfolio Compliance).
- Sana: Sana provides an enterprise AI knowledge platform that combines search, learning, and automation with deep app integrations. Overlaps with Nand AI's Magus platform and OneSearch product on enterprise-wide knowledge access and agentic workflows.
- Guru: Guru is an enterprise knowledge management platform with browser-extension-based delivery and AI-powered suggestions. Overlaps with Nand AI on permission-aware knowledge access and reducing time spent searching for information, though Guru's delivery model is lighter than Nand AI's agent platform.
Emerging players
- Coda AI: Coda combines documents, spreadsheets, and apps with embedded AI assistance. Its AI features (Coda Brain) overlap with Nand AI's knowledge-management use case, particularly for cross-system retrieval within collaborative documents, though Coda is more focused on productivity authoring than graph-grounded agent execution.
- Notion AI: Notion AI adds AI search and generation to Notion's workspace product. Notion is also a Nand AI integration target. Partial overlap with Nand AI's company-wide knowledge management segment but lacks the cross-system graph and enterprise permission inheritance.
- Box AI: Box AI adds AI-powered search, summarization, and content generation to Box's enterprise content management platform. Partial overlap with Nand AI's document-grounded retrieval and provenance, particularly for compliance-sensitive document workflows.
Broad incumbents
- Microsoft Copilot: Microsoft bundles Copilot across Microsoft 365, Teams, SharePoint, and Dynamics, and is also a Nand AI customer/integration partner. Copilot competes head-on with Magus and OneSearch in enterprise search and agentic workflows while leveraging bundled enterprise distribution that a standalone vendor cannot match.
- Google Gemini for Workspace: Google's Gemini integration across Workspace, Drive, and Cloud competes with Nand AI's cross-system search and agent capabilities. Bundled pricing and native indexing of Google Workspace content (a key Nand AI integration source) make Google a structural threat to standalone enterprise AI search vendors.
- Palantir Foundry: Palantir Foundry provides an enterprise data and decision platform with permission-aware ontology, agent workflows, and industrial/manufacturing deployments. Overlaps with Nand AI's vertical industrial and financial agent suites in heavy-asset, compliance-driven environments where audit trails and provenance are required.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat5 records
Key risks6 records
Key highlights7 records
Customer concentration
Nand AI compliance and trust
Trust signalCompliance1 record
Nand AI financial estimates
Financial estimateRevenue estimate
Valuation estimate
Nand AI leadership team
Management profileNumber of profiles
Profiles3 records
Nand AI funding detail
Funding detailFunding overview
Funding rounds1 record
Investors1 record
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Nand AI M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Nand AI
What does Nand AI do?
Nand AI builds and sells a Deterministic Context Engine for enterprise AI, delivered through its Magus execution-layer platform. The platform reconstructs enterprise knowledge as a continuously evolving knowledge graph that preserves authorship, hierarchy, versions, timelines, and cross-system relationships, then powers unified search (OneSearch) and specialized AI agents for sales, compliance, financial, and industrial workflows. Customers subscribe to Magus on tiered annual SaaS plans and deploy agents such as CPQ, RFP, DDQ, Market-Fit Analyst, Due Diligence, Portfolio Compliance, Proposal, and Supply Chain Resilience.
Is Nand AI a public or private company?
Nand AI is a private company. It is classified as venture growth investor backed and is currently operating.
When was Nand AI founded?
Nand AI was founded in 2023. It employs 11 to 50 people.
Where is Nand AI based?
Nand AI is headquartered in San Francisco, United States, in the North America region.
How does Nand AI make money?
One revenue line is on record: saaS Subscription (Magus Platform).
Who are Nand AI's main competitors?
Direct peers on record are Glean Technologies, Hebbia, Sana and Guru. Emerging players are Coda AI, Notion AI and Box AI. Broad incumbents are Microsoft Copilot, Google Gemini for Workspace and Palantir Foundry.
Does Nand AI have an API?
No public API is recorded for Nand AI.
What industry is Nand AI in?
Nand AI's product category is Enterprise AI Platform. Its primary akta.pro industry code is HDAEANAH, Enterprise AI Data & Knowledge Platforms (Vector Databases, Knowledge Graphs), with a secondary code of HDAAAKAD, LLM/GenAI Guardrails & Safety Controls (policy, filtering, routing). Its NAICS code is 5132 and its SIC code is 7372.