Zeroe

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Zeroe Zeroe
Zeroe

is the decision layer the AI stack is missing

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Where enterprise AI stalls

01

The decisions (judgement) that run a business, cross every function.

02

Good decisions need the whole picture.

facts & context

03

But no single business system sees the whole picture.

Some of the facts, some of the context — nothing synced.

04

because all business systems are isolated and ungoverned.

Sales · CRM
Finance · ERP
Ops · Email & docs
Planning · Spreadsheets
05

Business systems are missing a layer, that connects & governs all.

That's where Zeroe comes in…

Enterprisejudgement

Zeroe fills that gap - the decision layer.

Enabling all good judgement, from humans or soon, AI.

What 'judgement' is

It's tacit institutional knowledge that forms the missing context layer around enterprise decisions.

Why it's scarce

It lives in people, not systems. It doesn't transfer, doesn't compound, and leaves when they do.

What Zeroe does

Captures (encodes) judgment as it happens and turns it into an asset the enterprise owns and compounds.

How the market is changing

Industry knowledge is no longer an enterprise advantage.

Frontier models now hold more industry knowledge than almost anyone on an enterprise's staff. The expertise that used to separate companies is available to anyone who asks — and the gap closes faster every quarter.

Time Machine capability

Knowledge is no longer the edge. The advantage moved elsewhere.

Model capability is compounding; today's frontier, is a commodity within quarters.
The work models do, unsupervised, keeps doubling.

Where the advantage went

A frontier model knows the whole industry yet nothing about the specific company.

WHAT IT HAS
Flip
WHAT IT HAS
Every public fact about the industry
Instant recall, no fatigue
An answer to any question asked
WHAT IT LACKS
Flip
WHAT IT LACKS
The company's history, exceptions, and reasoning
The context behind every decision
The judgment the decision actually depends on.

Closing that gap is the whole game. It's where the advantage moved.

The asset created and destroyed

An enterprise makes thousands of expert decisions a year and keeps the value of none.

Value created, then lost. Thousands of times a year. Retained: zero

Every decision draws on judgment that took years to build. Nothing in the stack is built to capture it.

Why the systems don't catch it

The tech stack records what happened. Never why.

OUTCOME

Every system captures the outcome: the number, the status, the closed ticket.

CONTEXT

The context around it gets thinned: only 30 of the 60 fields enter, the other 30 are ignored.

JUDGMENT

And the judgment, the reasoning behind the decision, was never something these systems could capture.

Kept Thinned Never captured

The data is sitting in the systems. The judgment never made it in.

How Zeroe captures it

Zeroe encodes the decision.

Every decision is documented as it happens: a structured record, not a note.

CAPTURED AT DECISION TIME
STATEthe situation
ACTIONthe decision
RATIONALEthe reason given
ATTACHED WHEN KNOWN
OUTCOMEwhat happened next
RESULT
ONE RECORDZR-7F3A-22B6
The reasoning that was never a field, now the atom the platform is built on.

The model is interchangeable. The captured decisions stay.

Why it's defensible

One thin band is the firm's own. The rest is Zeroe's platform.

Surfaces — voice, chat, emailZEROE'S PLATFORM
Agent orchestrationZEROE'S PLATFORM
Firm-specific judgmentTHE FIRM'S
Model layerANY MODEL
Connectors / clean foundationZEROE'S PLATFORM

The firm's own judgment is the one band no one else can build — and it compounds with every correction. Zeroe owns the platform beneath it, that encodes that judgement, so the asset is never lost.

What the loop returns

Every decision carries its evidence and replays on demand.

Pull any decision the system made and the whole record is there. Nothing is a black box. Every correction promotes continuous improvement.

ONE RECORD · ZR-7F3A-22B6
INSPECTSee the state it saw, the call, and the reasoning behind it.
REPLAYRe-run the decision against what actually happened.
CORRECTThe human teaches it: right, wrong, why — and it folds back in.

How Zeroe chooses

Zeroe enters where four conditions hold.

01Fragmented dataThe systems don't talk, so the context is trapped.
02Low AI penetrationThe work is still manual — the gap is open.
03High decision frequencyEnough decisions that captured judgment compounds.
04Attributable outcomesYou can tell whether a call was right.

The industries Zeroe is in weren't chosen because they looked big. They were chosen because they pass the same filter.

Why it compounds

Every decision sharpens the next. That's the moat.

THE LOOP Judgement
encoded
1 Decision captured

The call and its stated reasoning.

2 Actual outcome

A record of what actually happened

3 The gap

Where the decision and actual outcome diverge

4 Decision folds in

The human teaches it: what is right, wrong, & why.

5 Sharper next call

Learning reinforced, next iteration improves continuously.

Each decision folds back in overnight. The longer it runs, the further ahead it gets.

Judgment trapped in people and fragmented systems

Same gap, every vertical

Why all at once

The same problem underneath every industry. One platform that fits them all.

Every industry connects to one core, built once: a shared data layer, capture mechanism, and workflow engine.

An AI-native approach to mapping data, workflows, and deployment stands a vertical up in weeks. Traction drives maturity from there.

One platform, many industries

Unrelated industries, the same trapped judgment.

DEPLOYED · LIVE Logistics An invoicing agent live in a customer sandbox: pulls shipment data from spreadsheets and email, verifies the three document signatures, flags exceptions to a human, pushes the invoice to accounting. BUILT IN TWO DAYS, FROM TWO CALLS
SIGNED LOI · 3
Logistics ecosystem partnerA vertically integrated cold-chain operator digitizing brokerage, warehousing, and trucking on one stack.
Financial servicesA channel into US credit unions — ~4,400 institutions holding ~$2.7T, almost none with the tooling to act on it.
EnergyA distributed-energy operator reconstructing asset-performance, warranty, and settlement by hand across telemetry, contracts, and engineering reports.
PIPELINE Hospitality · Healthcare · Insurance · Government services — arriving through ecosystem partners who already own the customer relationship.

Where the spend actually is

For every $1 of software,
$6 of work it never touches.

Software
$1
Work around it
$6reconciliation · chasing · manual stitching · the judgment calls
Value never captured
$6capacity consumed by the first $6

Vertical tools compete for the $1. Zeroe goes after the $12.

The verticals

Large decision verticals,
barely touched by AI agents.

VerticalMarketPenetration gapStage
Supply chain & logistics$2.6T US logistics cost<0.8% of agent tool callsDEPLOYED
Financial services4,287 credit unions ($2.43T) · 1,267 CDFIs · ~140 MDIs<4.0% of agent tool callsSIGNED LOI
Energy$500B solar PV · $2T clean-energy investment<3.0% of agent tool callsSIGNED LOI
Hospitality~$3.3T hotel operations spend<2% of agent tool callsPIPELINE
Insurance~$400B insurance operations market<3% of agent tool callsPIPELINE

Large verticals. Low penetration. A decision layer no one else is filling.

The landscape

Where agents work today,
and where the gap remains.

Most AI investment targets the intelligence layer. The unmet layer is the decision itself: the decision that crosses every system, that no tool today sees whole.

Model providersGive capability, not context. They make any single step smarter; the decision across the workflow isn't theirs to see.
Vertical agent toolsStrong in one narrow workflow, blind the moment a decision crosses systems and teams.
Agent observabilityShows engineers how agents behave. Doesn't capture the decision or the judgment behind it.
ZeroeThe layer across the stack — unifies the context, captures the judgment, and owns the decision none of the above can reach.

Leadership

Operator plus systems DNA.

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The raise

Raising $4M SAFE to scale
across proven verticals.

MetricCurrentPost-raise
ARR$350K$9.5M (proj.)
TCV$1.3M
Gross margin70%58.1% → expanding
Runway41 months
Breakeven ARR~$6.9M

Allocation

Product — the data-to-decision core for multi-domain, agent-ready deployments. GTM — product-led entry with direct and partner-led enterprise expansion. Talent — engineering and customer enablement at infrastructure scale.

Priced against the value it creates, not the seats it fills — a platform fee plus a share of the work and the outcomes it delivers.

For the probing reader

Appendix

Structural defensibility, the asset created and destroyed, why the systems miss it, and the return shape — the depth behind the skim.

How Zeroe grows is how it returns

Four verticals at once raises one question: how does this scale without fragmenting?

Zeroe enters through the player who already controls each vertical. The way that player is structured in, is the way value comes back to one core.

DIRECT

Zeroe enters and sells on its own.

Contract, data, and learnings — to the core, whole.
CHANNEL

A partner with leverage over a fragmented market drives adoption.

Zeroe holds every contract and all data — to the core, whole.
JOINT VENTURE

A partner whose own judgment is the moat co-builds the vertical.

Judgment sits in the JV; the core holds the platform license plus an equity stake.

One core · every route feeds it

The platform and the learnings that compound across every vertical.

Three routes in, one core out. The structure that wins the vertical is the structure that returns the value.

The wedges

Different entry points, same model.

LIVE
Logistics
Flip for details
Decision

Approve shipment pricing, scheduling and execution with compliance intact.

Who decides

COO · Head of Pricing · Head of Operations

What changes

Faster response, fewer failures, stronger proof for customers and finance.

Traction

US 3PLs & carriers across major semiconductor value chains.

IN PITCH
Financial services
Flip for details
Decision

Which segments to target, and how to expand lending while holding risk.

Who decides

Chief Growth Officer · Head of Retail Banking · Head of Member Growth

What changes

Higher conversion, better penetration, more efficient revenue growth.

Traction

Active proving contexts across banks and credit-union environments.

IN PITCH
Energy
Flip for details
Decision

Is underperformance operational failure or environmental variance?

Who decides

Asset Manager · Energy Ops Lead · CFO

What changes

Fewer disputes, better valuation, stronger credibility with investors.

Traction

A US solar operator on portfolio performance attribution.

What is actually needed

A layer above the stack to solve
two things, in order.

01Unify the foundation

Consolidate, clean, and structure all the data a company already holds — and, just as importantly, the context around it: the reasoning, conversations, and decisions that explain the numbers.

Not by replacing the systems it runs, but by reconciling them into one governed, traceable picture of operational truth.

02Encode the judgment

On top of that foundation, capture, apply, and improve the way the company decides — rather than leaving it in people's heads.

The foundation is what makes this trustworthy: there is finally something solid to encode judgment against.

Without the foundation, there's nothing trustworthy to encode judgment against. With it, judgment has something solid to run on.

What Zeroe is

The governed decision layer for enterprise.

The resource enterprises need to secure their competitive advantage: encoded judgment.

The connective layer

Consolidates and cleans the data and runs the feedback loops, then hands people improved information — carrying not just the facts but the context and evidence behind every recommendation.

ZR-8F39-7A21 data · logic · why — replayable

Auditable by default

A frozen record of what each decision relied on, and the recorded act of making and approving it. Replay the data, logic, and why — defensible to a regulator, auditor, or court, not a screen-share of what an agent did.

any model

Model-agnostic by design

Uses the right model per task, runs open-source models privately at a fraction of the cost, and hot-swaps to a better one without a rebuild. New businesses are configured in minutes, not weeks.

Decision-makers move faster and decide with confidence — and senior people spend their time looking forward, on analysis and efficiency, not backward on consolidation.

Zeroe

Context. Decisions. Confidence.

The governed decision layer for the AI era — encoding the judgment no model can reach.

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