Vivun researches
how AI teammates
achieve structured
reasoning.
Enduring memory and autonomous action — not just responses. We build the architecture that makes enterprise AI teammates think, not guess.
What Would It Mean
to Sell with an AI
Teammate?
Joe Miller, co-founder and Chief AI Officer at Vivun, explores the evolution from simple automation to AI agents that think, adapt, and partner with humans as true teammates. Twelve episodes on structured reasoning, enduring memory, and what genuine AI collaboration looks like in practice.
Our domain model
outperforms
foundational models.
Most AI models collapse under the weight of complex B2B reasoning. We built the architecture that doesn't — combining best-in-class foundational models with structured domain knowledge that holds fidelity across every reasoning hop.
solid = with ontology · dashed = without ontology · toggle above to isolate · higher = stronger logical reasoning
Inspectable.
Not opaque.
General-purpose AI produces plausible outputs. Vivun produces inspectable ones. Every system we build is grounded in structured domain knowledge — so enterprises can deploy AI with confidence rather than exposure. We define models. We set terms. We hold the standard.
read architecture paper →Structured Knowledge
Organizational truth — products, processes, competitive context — ingested into a persistent, queryable, auditable knowledge layer that agents reason from.
Sales Reasoning Engine
The SRM applies constrained logic to real selling situations — producing answers that can be verified against source material, not merely generated from pattern.
Live Delivery
The reasoning layer surfaces inside live selling moments — before, during, and after every customer conversation — where the outcome is still alive and movable.
We publish
what we learn.
Vivun's research advances the standard for enterprise AI — not to support a product roadmap, but because the field needs a clearer architecture. We define models. We set terms.
Beyond Automation: Why Enterprise AI Must Move Toward Structured Reasoning
Inspectability as Infrastructure: A Framework for Governable AI in Revenue Systems
The Domain Reasoning Model: Architecture, Constraints, and Deployment Patterns
What Revenue AI Gets Wrong: Confusing Pattern Matching with Contextual Intelligence
Structured Context vs. Retrieved Context: Why the Distinction Defines AI Reliability
The full research library — white papers, model definitions, deployment frameworks, and architectural perspectives.
AI that can be governed.
Not just used.
probabilistic
Domain knowledge, not general inference.
General-purpose AI infers from patterns across the internet. Vivun applies constrained logic within a defined, inspectable knowledge domain. The difference matters when the cost of a wrong answer is a lost deal.
opaque
Every answer has a source.
Every output traces back to the knowledge it was grounded in — so governance, legal, and InfoSec have full visibility into what the system knows and why it produced what it produced.
not_retrieved
Owned understanding, not borrowed similarity.
Context that is retrieved is borrowed. Context that is modeled is owned. Vivun builds domain models that give agents structured understanding — not vector search over documents.
novel
Built for the long deployment, not the demo.
We build for enterprise deployments that need to perform consistently across quarters, rep classes, and product generations — without requiring constant re-engineering to keep pace with novelty.
The platform,
in the field.
Hero is what the Vivun platform looks like when sellers need it most — an AI Sales Teammate grounded in the SRM, present inside live customer conversations.
AI Sales Teammate. Grounded in your products, your process, your deal context. Before, during, and after every customer conversation.