Vivun Navigation - AI Teammate for Sales
Agent Intelligence - Giving AI an Expert Sales Brain
Background
AGENT INTELLIGENCE

Everyone Built Chatbots.
We Built Cognition.

While others build RAG systems that treat every problem like keyword search, Vivun has pioneered the concept and execution of Agent Intelligence - the science of capturing and codifying human expertise. RAG agents are sophisticated parrots—they find and repeat chunks of text while missing the relationships that create real understanding. Vivun has solved the harder problem: transforming expert judgment into structured decision-making systems where every action is grounded in verifiable logic and explicit knowledge relationships.

Ava AI Sales Agent

Expert Knowledge

Declarative, procedural & tacit

1 Capture expert patterns
2 Structure knowledge
3 Generate responses

Sales Reasoning

Ontologies & graphs

1 Map relationships
2 Traverse paths
3 Generate conclusions

Structured Memory

Multi-layered reasoning

1 Context storage
2 Cross-learning
3 Optimize memory

Multi-Hop Logic

Auditable reasoning

1 Chain inferences
2 Bridge domains
3 Provide audit trail

We captured the brains of elite sellers.

Vivun Expertise Mapping
Patented Innovation

Patented Expertise.
Engineered for Scale.

How Vivun Learned to Map Domain Expertise

At Vivun, we didn't just build AI for sales—we pioneered a new way to capture and replicate domain expertise at scale which we call Agent Intelligence. We started by studying the world's best technical sellers—the people who make the impossible deals happen. We dissected their brainpower: the know-how, the tactics, the instincts they rely on every day.

Through thousands of hours of observation, analysis, and iteration, we uncovered the hidden patterns behind technical excellence—how top sellers qualify, handle objections, and connect product capabilities to real buyer pain. And we didn't stop there.

We built proprietary models to map this expertise into a structured intelligence system. Today, that system is known as the "Sales Reasoning Model" and it powers Vivun's AI Sales Agent, giving every rep access to the same elite thinking as the best technical sellers on the planet.

This isn't just innovation—it's invention. Our team holds patents on methods for mapping and operationalizing domain expertise, because no one else has done what we've done. We turned tribal knowledge into a transferable, scalable framework—making Vivun the true pioneer in the space.

Domain Mapping
Elite seller knowledge extraction and categorization
Pattern Recognition
Hidden tactics and decision frameworks
Expertise Transfer
Tribal knowledge into scalable AI models
Scalable Intelligence
Every rep gets elite-level thinking
Patent Badge Rectangles
US PATENT
Text Processing
11,853,698
Granted
US PATENT
Gap Clustering
11,354,505
Granted
US PATENT
Trial Management
11,861,330
Granted
Ava vs RAG - Intelligence Comparison
INTELLIGENCE COMPARISON

Not all AI Agents are Created Equal

RAG agents help you find what happened. Ava helps you decide what to do next.

AVA INTELLIGENT
Strategic Question
"How do we win this deal?"
Multi-Framework Analysis
Expert reasoning patterns
Knowledge Integration
Contextual understanding
Strategic Actions
Clear next steps to win
RAG RETRIEVAL
Same Question
"How do we win this deal?"
Database Search
Finding similar text
Text Snippet
Past transcript excerpt

The Critical Difference: While RAG retrieves information, Ava reasons through problems. It's the difference between a search engine and a strategic advisor.

Toggle Section - Actionable Outputs

Actionable Outputs, Not Search Results

RAG Output
Ava Output
"I found notes about winning deals..."
[Transcript snippets]
"Here's the actionable path to win: Demo with champion, resolve IT objection."
[Cited from Calls & CRM]
What You See vs What You Get - Vivun
BENEATH THE SURFACE

What You See vs What You Get

The real difference is beneath the surface: only one agent thinks like a domain expert

RAG Agent

RETRIEVAL
"How do we win this deal?"

I found the following conversation on a call with [Sales Rep] about how they plan to win this deal this quarter.

Covers entire account, lasts 90 days

How RAG searches:

  • Uses LLM as a mouthpiece for answering, not as the reasoning engine
  • Finds text chunks from transcripts that match keywords from the prompt
  • Gathers transcript snippets discussing "winning the deal"

Ava

INTELLIGENT
"How do we win this deal?"

You can win this deal by following these Actionable Next Steps…

Here's my current understanding of the deal… this is the Decision Criteria & what matters most… here are the key objections and how I would address them…

Citations from call transcripts, Slack, email, CRM

How Ava reasons:

  • Determines which concept and memory types the user needs
  • Prioritizes the most relevant memories and connects key concepts via knowledge graphs
  • Gathers context-rich memories and makes strategic decisions

The Critical Difference: RAG retrieves what was said. Ava understands what to do.

Four Tenets of True Enterprise AI - Vivun
SECURE INTELLIGENCE

The Tenets of True Enterprise AI

Beyond Reactive AI — Ava Thinks and Works Ahead, and Securely

Expertise & Reasoning
True intelligence is more than pattern matching. Ava is modeled on expert workflows, delivering context-aware reasoning you can trust.
Memory
Ava remembers and builds context across interactions, making every output informed, accurate, and personal.
Proactivity
Stop waiting on prompts. Ava anticipates what's next and acts, delivering work that moves deals forward before you ask.
Data Security
Your data stays yours. We never train on client data or interactions—ensuring complete isolation and enterprise-grade security.

Four pillars. One unified intelligence that transforms how sales teams work.

Enterprise Data Privacy - Vivun
Enterprise Data Architecture

Your Data Builds Your Advantage, Not Ours.

Privacy Architecture

Guaranteed Data Sovereignty

Unlike AI platforms that use your data to train shared models, Vivun ensures your competitive edge stays isolated and encrypted within your infrastructure.

Data Isolation
100% Private
Model Training
Zero Sharing
Competitive Intel
Stays Yours
Technical Implementation

Ava Space: Isolated AI Environment

Every interaction improves your own AI Agent inside your secure Ava Space. Your learnings never leave. Your competitive edge compounds exclusively for you.

  • Environment Dedicated, isolated AI workspace
  • Learning Model Private accumulation of insights
  • Data Flow Unidirectional, never external
  • Intelligence Compounds within your domain
Zero Third-Party Access Protocol

We do not allow your data to be accessed, transmitted, or received by any third party without your explicit consent.

Other AI Vendors
vs
Vivun Architecture

Shared Intelligence Model

× Global training pools dilute competitive edge
× Your insights shared across all customers
× Data used to improve competitor advantages

Private Intelligence Model

Private Ava Space - isolated environment
Zero data leakage - your edge stays yours
Advantages compound over time, privately
Intelligent Agents Video Series - Vivun SRM
AI MASTERCLASS SERIES

Intelligent Agents: A New Species of Coworker

Vivun's Chief AI Officer, Joe Miller, explains why RAG approaches fall short and how ontologies enable true AI reasoning.

Why RAG Isn't Enough: The Power of Ontologies & Knowledge Graphs

Duration: 3:50
Joe Miller, Chief AI Officer

Why RAG Falls Short

Limitations of treating problems as search

Knowledge Graphs

Structured definitions enable reliable reasoning

From Chunks to Concepts

Moving beyond text to understanding

Expert Systems

Domain expertise in AI frameworks

"The future of work isn't just faster or more automated—it's more human, because that's what we're designing agents to be."
— Joe Miller, Chief AI Officer
Sales Reasoning Model - Vivun
DEEP DIVE

Sales Reasoning Model:
Learn How Ava Thinks

See how Vivun used 'Agent Intelligence' to map the expertise of the world's top sellers, building Ava's proprietary Sales Reasoning Model. Through this SRM, Ava goes beyond traditional AI by using structured intelligence to deliver the next evolution in autonomous sales execution.

Structured Intelligence

Beyond pattern matching to true reasoning

Transparent Logic

Every decision traced back to sources

Autonomous Action

Proactive work generation without prompts

High-Stakes Decisions - Sales Reasoning Model
Because in sales, close enough isn't close enough

Sales Can't Afford AI That Guesses

Generic AI might work fine for writing poetry or summarizing documents. But sales happens in high-stakes environments where wrong moves kill deals, damage relationships, and cost revenue.

Misjudge stakeholder priorities

Deal stalls for months

Wrong timing on pricing

Competitor wins

Miss buyer signals

Opportunity dies

Poor follow-up execution

Relationship damaged

Why Language Models Break Down in Sales

Most AI sales tools are built on language models trained on everything from Reddit posts to academic papers. They know about sales, but they don't know how to sell.

Core Issue: No Sales Ontology

  • Confuses Champions, Economic Buyers, Decision Makers, and Influencers — can't map the buying committee
  • No understanding of stage-appropriate actions vs. generic sales activities — suggests wrong moves at wrong times
  • Can't distinguish between real objections and negotiation tactics or stall behaviors — misreads buyer intent
See 4 Additional Critical Limitations
Methodology • Psychology • Timing • Reasoning

No Sales Methodology

No understanding of MEDDICC, Challenger, or proven frameworks — gives generic advice instead of structured playbooks

No Buyer Psychology

Can't read between the lines or interpret stakeholder dynamics — misses political undercurrents

No Timing Context

Doesn't understand deal cycles, urgency, or competitive windows — suggests moves at wrong moments

Compounding Errors

Auto-regressive reasoning leads to drift over complex decision chains — compounds mistakes

AI That Already Knows How to Sell

Ava shows up Day 1, knowing how to sell and how YOU sell. She can help you strategize your way to close and automate your way to total process compliance.

  • Learns your unique sales approach and methodology
  • Strategizes deal progression based on your process
  • Automates compliance with your sales framework
  • Adapts to your team's specific selling style
  • Transparent reasoning you can audit and trust
Expert Knowledge
Sales methodology encoding
Strategic Logic
Decision frameworks
Deal Memory
Context persistence
Transparent Reasoning
Auditable decisions

See Expert Reasoning in Action

Watch how Ava applies the Sales Reasoning Model to navigate a complex enterprise deal—from stakeholder analysis to competitive positioning to closing strategy.

Meet Ava
The Minds Behind Ava's Brain - Vivun
AI PIONEERS

The Minds Behind Ava's Brain

Ava's intelligence is built upon decades of groundbreaking research from the world's most visionary AI pioneers

Amir Bakarov

Amir Bakarov

Sr. Machine Learning Engineer

Craig Baker

Craig Baker

Lead Site Reliability Engineer

Mark Baltzegar

Mark Baltzegar

Director, Engineering

Brad Bouldin

Brad Bouldin

Principle Engineer

John Bruce

John Bruce

CTO

Chris Bruner

Chris Bruner

VP of Product

Sergey Buciuscan

Sergey Buciuscan

Lead Software Development Engineer

Jon Call

Jon Call

Sr. Engineering Manager

Shine Chaudhuri

Shine Chaudhuri

Lead Product Designer

Phil Chwistek

Phil Chwistek

Sr. Product Manager

Ryan Conklin

Ryan Conklin

Lead Software Development Engineer

Rachel Duchesneau

Rachel Duchesneau

Sr. Software Engineer

Iyobo Eki

Iyobo Eki

Lead Software Engineer

Melodie Hauck

Melodie Hauck

Customer Support Engineer

Danielle Heffernan

Danielle Heffernan

Customer Experience Manager

Rayne Hernandez

Rayne Hernandez

Sr. Machine Learning Engineer

Brian Johncox

Brian Johncox

Software Engineer

Kate Kravchyshyn

Kate Kravchyshyn

Sr. Software Engineer

Dawid Kulig

Dawid Kulig

Staff Software Engineer

Chen Liang

Chen Liang

Sr. Machine Learning Engineer

Dennis Lin

Dennis Lin

Lead Machine Learning Engineer

Brian Mckean

Brian Mckean

Lead Software Engineer

Leonel Mena

Leonel Mena

Software Developer

Joe Miller

Joe Miller

Chief AI Officer

Logan Miller

Logan Miller

Sr. Cloud Security Engineer

Kevin Perrine

Kevin Perrine

Staff Software Engineer

Alanna Regan

Alanna Regan

Sr. Product Designer

John Salvatore

John Salvatore

Principle Engineer Architect

Shrey Shah

Shrey Shah

Sr. Software Engineer

Volodymyr Sokol

Volodymyr Sokol

Lead Software Engineer

Dan Stone

Dan Stone

Lead Software Engineer

Vitaliy Tomkiv

Vitaliy Tomkiv

Sr. Software Engineer

Mark Ward

Mark Ward

Lead Machine Learning Engineer

Russell Witham

Russell Witham

Director, Product Management

Ryan Woodcox

Ryan Woodcox

Staff Software Engineer