Sales Engineering

Sales Engineering with Precision, Not Guesswork

Automate the technical heavy lifting of the sales cycle. Reconstruct complete context across engineering specs, past pilots, and product documentation to drive the technical win.

Problem & Impact

The Sales Engineering Bottleneck: Hunting for Context

Sales Engineers spend up to 40% of their week playing information detective.

  • Critical technical answers are buried in Slack threads, Jira tickets, or locked in PM inboxes

  • Fragmented data leads to over-promising that engineering cannot deliver

  • Using outdated P&IDs or security policies increases liability and deal friction

Traditional tools surface files. They don’t surface the truth.

| In high-stakes deals, technical ambiguity kills trust.

Nand AI Workflow

The Foundational Context Engine for Sales Engineering

Nand AI doesn’t just index technical docs. It reconstructs their relationships.

The Context Engine becomes the system of record for your firm’s technical intelligence.

  • Graph-First Technical Mapping
    Link hardware constraints in a BOM to commercial terms in Salesforce.

  • Timeline & Version Intelligence
    Distinguish beta documentation from supported production versions.

  • Provenance-Backed Proof
    Every customer-facing answer links to its source and approving engineer.

What this enables

Technical Answer Synthesis

Don’t just find documents. Construct the truth.

Traditional search returns lists of PDFs. Nand AI synthesizes answers across systems with deterministic proof.

KEY CAPABILITIES
  • Multi-Source Aggregation
    Combine specs, Slack confirmations, and tickets into a single response.

  • Deterministic Citations
    Hover to see source, author, and timestamp.

  • Conflict Detection
    Flag contradictions instead of hallucinating.

Agentic Workflows

For the Technical Win

Deploy agents that handle high-stakes technical workflows with speed, traceability, and control.

Agent 1

Technical RFP Agent

Deconstructs RFI/RFPs and auto-drafts responses based on validated engineering specs.

Primary Outcome: 50% faster bids with zero engineering bottlenecks.

Agent 2

Solution Config Agent (CPQ)

Generates approval-ready quotes with built-in margin and feasibility validation.

Primary Outcome: Zero errors in technical configurations.

Agent 3

Compliance & Security Agent

Maps customer security requirements (ISO, SOC2, HIPAA) to internal evidence.

Primary Outcome: Reduced review cycles and shorter time-to-close.

Deep Dive

The Pilot-to-Production Handover

The most dangerous moment in a deal is the transition from pre-sales to implementation.
Nand AI automates this by creating a Contextual Blueprint.

01

Automated Briefing

Generate a State of the Union report from pilot Slack, specs, and Q&A logs.

02

Commitment Tracking

Flag every custom promise and edge case discussed.

03

Instant Onboarding

Ask the Context Engine about pilot requirements & get answers instantly.

One Graph. Infinite Context.

The Nand AI Context Engine isn't hardcoded. It adapts its schema dynamically to the unique constraints of your industry.

01.

Industrial Tech

Understands P&IDs, BOM hierarchies, and complex equipment specifications automatically.

02.

Legal Tech

Maps citations across thousands of case files, contracts, and regulatory PDFs with precision.

03.

Financial Services

Traces audit trails across transaction logs, policy documents, and communication records.

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.

  • Tenant-Isolated Architecture
  • Zero-Training Guarantee
  • (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 automate the technical win?

The next generation of Sales Engineering won’t be built on prompts and patches. It will be built on context.