WHAT WE BELIEVE

For high-stakes decisions, trust is the currency that matters most

Everyone can agree that for AI to scale in manufacturing, accuracy, proof of value, strength of data, and workflow integration are paramount. We agree with all of this too. However, for high-stakes decisions, solving these points alone won’t earn enough trust to drive adoption. That gap is what led us to our convictions.

Our Convictions:

The answer isn’t smarter AI, it’s smaller AI

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The answer isn’t smarter AI, it’s smaller AI

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The answer isn’t smarter AI, it’s smaller AI

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Messy data isn’t why your AI pilot failed

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Messy data isn’t why your AI pilot failed

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Messy data isn’t why your AI pilot failed

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Great AI shouldn’t need great questions

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Great AI shouldn’t need great questions

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Great AI shouldn’t need great questions

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Automate the checks, not the calls

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Automate the checks, not the calls

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Automate the checks, not the calls

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Docs alone won’t preserve tribal knowledge

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Docs alone won’t preserve tribal knowledge

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Docs alone won’t preserve tribal knowledge

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These are our convictions, we'd love to hear yours.

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HOW VERIAN WORKS

No black boxes. Just decisions and outcomes you can follow.

VERIAN operates inside defined boundaries, grounds decisions in operational data, surfaces what it’s missing, and improves over time. Here’s a closer look at how a decision moves from a question to a defensible answer, and what happens when VERIAN doesn’t have everything it needs.

VERIAN’s Workflow

Inputs

Ground Truth

Systems of record, documentation, and sensing & control systems

Operational Truth

Org norms, team practices, and human expertise

VERIAN

Builds steps for each defined use case

Assembles and validates context

Reasons through the steps & cites sources

Decision

Release:
Checks validated

and passed

Hold:

Checks validated

and failed

Gap:

Missing context, prompts review

Gap → request additional context → update inputs

VERIAN’s Workflow

Inputs

Ground Truth

Systems of record, documentation, and sensing & control systems

Operational Truth

Org norms, team practices, and human expertise

VERIAN

Builds steps for each defined use case

Assembles and validates context

Reasons through the steps & cites sources

Decision

Release:
Checks validated

and passed

Hold:

Checks validated

and failed

Gap:

Missing context, prompts review

Gap → request additional context → update inputs

VERIAN’s Workflow

Inputs

Ground Truth

Systems of record, documentation, and sensing & control systems

Operational Truth

Org norms, team practices, and human expertise

VERIAN

Builds steps for each defined use case

Assembles and validates context

Reasons through the steps & cites sources

Decision

Release:
Checks validated

and passed

Hold:

Checks validated

and failed

Gap:

Missing context, prompts review

Gap → request additional context → update inputs

Every decision, made defensible.

Most AI gives you an unreliable answer. VERIAN gives you a defensible record: complete with the decision, the reasoning, and the supporting context. When an expert user applies judgment to a record, VERIAN asks whether that judgment should carry forward to inform future calls.

No matter the decision made, VERIAN ensures you can stand behind it months later.

HOW IT’S DIFFERENT

In a market full of capable AI, seek the one that knows its limits.

Manufacturers evaluating AI today are largely choosing between three approaches. All three are capable, yet none of them were built with auditability and constraint top of mind. That’s the gap VERIAN is built to close.

General AI assistants

The fastest to deploy, typically a licensed foundational model with data access constrained for security.

Connected AI with RAG

The same foundational models, now hooked into existing systems so they can retrieve real context, protected by enterprise agreements.

Fine-tuned vertical models

An off-the-shelf model trained on domain and internal data, built in-house or by a specialist vendor, with data protected by design.

How VERIAN compares with leading AI categories:

Legend: ○ no capabilities ◐ partial capabilities ● full capabilities

General AI
Assistant

Connected AI
with RAG

Fine-tuned
Vertical Model

VERIAN

Uses a natural-language interface

●

Works across structured & unstructured data

●

Connected to operational data

○

●

Quickly retrieves relevant info

○

●

Brings deep industry & domain knowledge

○

◐

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Stands up to an audit

○

◐

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Safely stops when missing context

○

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Scope

Truly unconstrained

Typically constrained with light guardrails

Constrained in target industry / scope

Only for what it’s explicitly built for

Constraint is the feature.

For high-stakes decisions, you don’t need the model with the greatest breadth. We believe the correct model will be the one that performs exactly as predicted, and that’s what we’re building with VERIAN.

HOW WE WORK WITH YOU

VERIAN delivers results in weeks, not an 18-month implementation roadmap.

We believe successful programs are those that start small, and are purposefully architected to scale. That belief guides our approach: clear use cases, real operational data, and measurable value without needing to boil the ocean.

PHASE 1

Use Case Alignment

Joint alignment on high-n use cases embedded in the right complexity, with the right team members mobilized from day one. This is about hitting the ground running, not a consulting exercise.

Use case selected

PHASE 1

Use Case Alignment

Joint alignment on high-n use cases embedded in the right complexity, with the right team members mobilized from day one. This is about hitting the ground running, not a consulting exercise.

Use case selected

PHASE 1

Use Case Alignment

Joint alignment on high-n use cases embedded in the right complexity, with the right team members mobilized from day one. This is about hitting the ground running, not a consulting exercise.

Use case selected

PHASE 2

Deploy

We hook up the right data sources so VERIAN works from real operational data. The architecture is set up to scale without a boil-the-ocean data lake implementation.

Real data connected

PHASE 2

Deploy

We hook up the right data sources so VERIAN works from real operational data. The architecture is set up to scale without a boil-the-ocean data lake implementation.

Real data connected

PHASE 2

Deploy

We hook up the right data sources so VERIAN works from real operational data. The architecture is set up to scale without a boil-the-ocean data lake implementation.

Real data connected

PHASE 3

Grow

We track usage, decisions enabled, and the ratio of gaps in context shrinking. Data shapes which use cases come online next so value can grow month to month.

Value measured

PHASE 3

Grow

We track usage, decisions enabled, and the ratio of gaps in context shrinking. Data shapes which use cases come online next so value can grow month to month.

Value measured

PHASE 3

Grow

We track usage, decisions enabled, and the ratio of gaps in context shrinking. Data shapes which use cases come online next so value can grow month to month.

Value measured

Ready to start Phase 1?

You’ve seen the plan: align on the right use case, deploy in weeks, and grow from there. We’re looking for visionary operators who share our beliefs and are serious about putting AI to work in operations. If you’re interested in having a conversation and learning about early access, let’s talk.

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