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Spotonix

FIRST MEETING · 30 MIN

THE AGENTIC BI ANALYST · BUILDS YOUR CONTEXT GRAPH

Your Concierge Analyst that
learns · composes · compounds
with your business.

Reads your warehouse, dbt models, and every SQL your team has ever run. Composes verified plans from your validated Segments and Calculations. Same plan compiles to the same SQL — math, not probability.

LEARNS your business

Your warehouse, your dbt models, your team's vocabulary. Speaks back in measures, segments, hierarchies — not column names.

COMPOSES the plan

Builds from validated Segments and Calculations — not from scratch. Plan visible before SQL runs.

COMPOUNDS with every Q

Every verified answer joins your Context Graph. The 100th question is faster than the 10th.

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THE PROBLEM

Self-service BI is an
illusion of competence.

Dashboards

Trusted · Rigid

Pre-built views. Break on novel questions.

Breaks on novel questions

SQL Notebooks

Flexible · Siloed

Flexible but siloed. Knowledge walks out with the analyst.

Context walks out the door

Text-to-SQL

Fast · Opaque

Generates from scratch every time. Different SQL Mon vs Tue.

Context never forms

ChatGPT · Claude

Brilliant · Stateless

Brilliant. Stateless. No memory of your business.

No memory of your business

LLMs have solved natural language. The missing layer is a Context Graph — the structured record of how your business actually reasons about its data.

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WHAT WE DELIVER

A Context Graph,
constructed from your business.

YOUR DATA

Schema, joins, profiles, data quality.

Read once, enriched continuously. The system understands the shape of your warehouse before any question gets asked.

YOUR LOGIC

Measures, segments, hierarchies, vocabulary.

Captured as first-class business primitives. The things your team already says — promoted to the system's native nouns.

YOUR HISTORY

Past queries, validated answers, team decisions.

Persisted as reusable assets. Every accepted plan adds to the graph — the institutional knowledge stops walking out the door.

The Context Graph is yours alone. Portable. Sovereign. Growing.

SPEAKER NOTES — SLIDE 3 · 90 SEC · NEEDLES: OWNER COMMITMENT + DATA-LEADER RISK

"This is the deliverable. Not a chat tool, not a chart tool. A structured representation of how your business reasons about data. Three layers."

"Your data. Schema, joins, table profiles, data-quality observations. Read once, enriched continuously."

"Your logic. The measures, segments, hierarchies, and vocabulary your team already uses — captured as first-class business primitives. The things you say in meetings get promoted to nouns the system natively understands."

"Your history. Past queries, validated answers, team decisions — persisted as reusable assets. This is where most BI tools leak; we close that leak."

"The line I want you to remember: we build it day one, you own it forever, it gets denser every week."

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HOW IT WORKS

Understand. Interpret. Compound.

UNDERSTAND

Reads your warehouse.

Enriches schema, ingests prior SQL, encodes your team's vocabulary. The Context Graph is seeded before any question gets asked.

INTERPRET

Compiles to BI Algebra.

The LLM proposes a symbolic plan in BI Algebra over your Segments and Calculations. The plan is accepted only if the algebra closes — producing an Answer that joins your Context Graph.

COMPOUND

Persists every verified answer.

Back into your Context Graph. The next question is faster, sharper, and already trusted — because the search has more to compose from.

Same plan → same SQL. Math, not probability.

SPEAKER NOTES — SLIDE 4 · 90 SEC · NEEDLE: ANALYST SKEPTICISM

"Three steps under the hood."

"Step 1, Understand. The system reads your warehouse, enriches the schema, ingests prior SQL, encodes your vocabulary. This is what every BI vendor tries to do."

"Step 2, Interpret. This is where we replace probability with algebra. The LLM doesn't write SQL — it proposes a symbolic plan in BI Algebra, composed over your Segments and Calculations. We accept the plan only if the algebra closes — meaning every concept resolves to something validated. The result is an Answer that joins your Context Graph. If the algebra doesn't close, we refuse and ask. This is why I can promise that the same plan gives the same SQL every time."

"Step 3, Compound. Every verified answer persists back to the Context Graph. The part nobody else has — every answer makes the next one faster."

"The line: same plan, same SQL. Math, not probability."

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WHY WE WIN · THE MOAT

Three pillars.
All three are required.

YOUR CONTEXT GRAPH

Yours to compound.
Not theirs to ship.

Built from your schema, your queries, your BI assets. Compounds every time you use it. The asset is the moat — and the moat is yours.

ALGEBRAIC VERIFICATION

The system refuses
instead of inventing.

No probabilistic guessing. Ambiguous questions are refused. Data-quality issues are surfaced without being asked. Every executed query has a verified plan attached: audit trail by construction.

BACKEND-AGNOSTIC

LLM is interchangeable.
Plan is the substrate.

Tested today on OpenAI and Anthropic. Run on your enterprise contract. Swap GPT, Claude, or an open-weight model — the plans still close, the SQL still compiles.

Each pillar exists elsewhere in pieces. The hard part is all three operating together in one workflow.

SPEAKER NOTES — SLIDE 5 · 90 SEC · NEEDLES: OWNER COMMITMENT + DATA-LEADER RISK

"You'll see vendors with pieces of this. Pillar 1 alone is a feature. Pillar 2 alone is a tech demo. Pillar 3 alone is a procurement memo. The hard part is all three operating together in one workflow — that's the product."

"One. Your Context Graph is built from your schema, your queries, your BI assets. It compounds the moment you start using it — the asset is the moat, and the moat is yours."

"Two. Algebraic verification. The plan only runs if the algebra closes. No guessing. If something's ambiguous, the system refuses — you'll see that in the demo. The system also surfaces data-quality issues without being asked. Audit trail is built into the architecture, not bolted on."

"Three. Backend-agnostic. The LLM is interchangeable — we can swap it. Tested today on OpenAI and Anthropic; you run on your own enterprise contract. The plan is the substrate. This is why we win on procurement."

"We'll show all three live in 60 seconds."

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WHAT COMPOUNDS

What looks like a tool on Day 1
becomes infrastructure by Quarter 2.

DAY 1

First trusted answer.

Connect warehouse. Context Graph seeded from history. Self-serve answers within an hour.

WEEK 4

Knowledge persists, not people.

100+ Segments and Calculations validated. New analysts onboard against living context.

QUARTER 2

A compounding institutional asset.

1,000+ validated answers. Audit-ready. Survives reorgs and departures.

The asset is yours — portable, sovereign, growing.

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BRIDGE TO LIVE DEMO

Let me show you
on real data.

Empty Context Graph · TPC-DS dataset.

Three real questions about habitual buyers.

Watch what gets reused from question to question.

If it works the way I described, the demo proves it. If it doesn't, you'll see that too.

SPEAKER NOTES — SLIDE 7 · 30 SEC · NEEDLES: ANALYST SKEPTICISM + OWNER COMMITMENT

"Public benchmark, no cherry-picking. TPC-DS is the standard analytical benchmark; anyone who's worked in BI has seen it. The schema is rich enough to support real analytical questions."

"Three things to watch for. Empty Context Graph at the start — you'll see it build. Three questions about habitual buyers, each more sophisticated than the last. And watch what gets reused from question to question — the second answer composes from pieces of the first; the third composes from both. Reuse is the trust signal, not raw latency."

"If a refusal naturally surfaces during the demo, call it out live as a trust signal — but don't promise one on the slide; it's hard to reliably stage in a single session."

"Switching to live screen share now. Demo script: docs/sales/wow-demo-tpcds.md."

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THE BUSINESS QUESTION

Two things to take back
to your team.

WHO BENEFITS

Business owners get a Monday-morning review without waiting on analysts.
Analysts get back 50%+ of their week from ad-hoc tickets.
Data leaders get an audit-ready, defensible BI surface.

WHAT IT REPLACES

Dashboard sprawl — cuts 30–60% maintenance load.
Ad-hoc analyst requests — cuts cycle 3–10×.
Text-to-SQL pilots — replaces with verified, governed architecture.

The question to ask your team isn't "do we need this?"
It's "what would we stop doing if this worked?"

SPEAKER NOTES — SLIDE 8 · 90 SEC · NEEDLES: OWNER COMMITMENT + DATA-LEADER RISK

"Before we talk about what we'd do together, let's name what changes for the people in your org and what budget line this affects. Both of those are answerable today."

"Who benefits. Business owners stop waiting in the ticket queue — trusted answers Monday morning. Analysts get half their week back from ad-hoc work — they go back to strategic projects and mentoring. Data leaders get governance that survives ad-hoc demand instead of collapsing under it."

"What it replaces. Dashboard sprawl — you cut 30 to 60 percent of maintenance load on stale views. Ad-hoc analyst requests — you compress cycle time 3 to 10x. And text-to-SQL pilots — you replace probabilistic SQL generation with a verified, governed architecture."

"The parting question, the one I want you to take to your team: not do we need this, but what would we stop doing if this worked?"

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THE ASK

A two-week scoping pilot.
On your data. No paid contract.

WHAT WE NEED FROM YOU

One read-only warehouse credential
30 min of your data team's time, once
One hour with two business users
An NDA you already have a template for

WHAT YOU GET IN 2 WEEKS

Your Context Graph, built from your data
Three trusted answers your team validated
Quantified ROI projection
Go / no-go decision with zero sunk cost

“This is not the LLM's answer. This is the verified plan the LLM proposed,
that the system accepted only because the algebra closed.”

founders@spotonix.com · book a 30-min call · spotonix.com/architecture

Your Concierge Analyst that learns · composes · compounds with your business.

Self-service BI is an illusion of competence.

A Context Graph, constructed from your business.

Schema, joins, profiles, data quality.

Measures, segments, hierarchies, vocabulary.

Past queries, validated answers, team decisions.

Understand. Interpret. Compound.

Reads your warehouse.

Compiles to BI Algebra.

Persists every verified answer.

Three pillars. All three are required.

Yours to compound.Not theirs to ship.

The system refusesinstead of inventing.

LLM is interchangeable.Plan is the substrate.

What looks like a tool on Day 1 becomes infrastructure by Quarter 2.

Let me show you on real data.

Two things to take back to your team.

A two-week scoping pilot. On your data. No paid contract.

Your Concierge Analyst that
learns · composes · compounds
with your business.

Self-service BI is an
illusion of competence.

A Context Graph,
constructed from your business.

Three pillars.
All three are required.

Yours to compound.
Not theirs to ship.

The system refuses
instead of inventing.

LLM is interchangeable.
Plan is the substrate.

What looks like a tool on Day 1
becomes infrastructure by Quarter 2.

Let me show you
on real data.

Two things to take back
to your team.

A two-week scoping pilot.
On your data. No paid contract.