Axiom Workshop
Half day · Free

Half a day on your real data with the solution architects who would lead the Axiom build, ending with a draft entity model in your hands.

A working session with the solution architects who would lead the engagement. Not a sales pitch, not a maturity assessment. You score your data domains against the criteria that decide whether a semantic layer pays off, build a draft entity model for one real domain, and see Axiom resolve a query across your actual source systems. By the end you know whether to schedule the full build.

Half day Free Your actual data Engineers run it Draft entity model output

Book the Axiom Workshop →

Why this workshop exists

A semantic layer either works on your data or it doesn't. The only way to find out is to try it on your data.

Demos on clean schemas prove nothing. The standard benchmarks (BIRD, Spider) score AI agents at 80 to 90% on 10-table academic datasets and drop to single-digit accuracy on real enterprise schemas with hundreds of tables and the column names twelve teams left behind.

Your data is different. Your schemas are different. Your naming conventions were designed by six teams over twelve years, and nobody wrote down the rules.

NHS Wales had the same problem on a public-health dataset spread across multiple systems. We built the platform in two weeks. Policy makers now get answers in two minutes instead of days, with HIPAA-grade lineage on every query and accuracy good enough to brief ministers from.

Not a simulated environment. Not a sanitized demo. Your data, your domains, your edge cases.

90% vs 6%

The accuracy gap between clean demos and real enterprise schemas. Academic benchmarks on 10 tables vs production systems with 500+ tables and cryptic naming.

4 hrs hands-on

Four sessions, each building on the last. Domain scoring, entity modeling, architecture mapping, and an honest go/no-go conversation.

1 draft entity model

You leave with a working artifact. Entity definitions, relationship maps, and metric logic for one real domain. Not a slide deck.

What you'll do in four hours

Four sessions across four hours, working through your actual data, ending with a go or no-go answer.

0:00 – 1:0060 min

Domain scoring

Score your own data domains against our readiness criteria. Which domains have the worst naming conflicts? Where do your agents get the most wrong answers? Which systems have the most schema drift? You'll rank them by impact and readiness so the rest of the workshop focuses on the domain that matters most.

1:00 – 2:3090 min

Entity modeling Hands-on

Build a draft entity model for one real domain together. Your data engineers and ours, working through entity definitions, relationship maps, and metric logic for the domain you picked in session 1. You'll see how Axiom resolves the ambiguity that breaks your current agent queries.

2:30 – 3:3060 min

Architecture walkthrough

Map the three Axiom layers (Semantic, Kinetic, Dynamic) to your specific AWS infrastructure. Which source systems connect through the kinetic layer? What governance policies does the dynamic layer need to enforce? You'll leave with a clear picture of how Axiom would deploy in your environment.

3:30 – 4:0030 min

Go / No-go

Honest conversation. Is the full build the right next step? We'll tell you if it's not. If the complexity is too low, if the source systems aren't ready, if the problem is upstream of a semantic layer, we'll say so. You don't need another vendor telling you what you want to hear.

What you leave with

An artifact, not a slide deck.

01. Domain readiness scorecard

Your data domains ranked by AI-readiness, with specific gaps identified per domain.

02. Draft entity model

A working entity model for one priority domain, showing entity definitions, relationships, and metric logic.

03. Architecture map

Axiom's three layers mapped to your AWS infrastructure, with source system connections and governance requirements identified.

04. Go/no-go recommendation

Our honest assessment of whether Axiom is the right fit for your data complexity and agent ecosystem.

Every output is yours. Whether you proceed with the full build or not.

Who should be in the room

Bring the people who know your schemas best, and the people who would have to defend the numbers a semantic layer produces.

Data Engineering Lead

Must attend

Knows the schemas, the naming conventions, the tribal knowledge.

AI / ML Lead

Must attend

Knows how agents are querying data today.

CTO or VP Engineering

Recommended

Decision-maker who'll approve the full build.

Data Domain Owner

Recommended

The person who can say "that definition is wrong" for the priority domain.

Total: 3–6 people. Small enough to do real work. Big enough to represent the data landscape.

Book the workshop.
Four hours, four sessions,
one honest answer.

No commitment beyond the half day. No contract. No follow-up pressure. You'll talk to engineers who've built semantic layers on AWS. You'll work on your actual data. You'll leave with a draft entity model and an honest answer about whether Axiom is right for your infrastructure.

Book the Axiom Workshop →

Or talk to an engineer first. Not a sales exec.

Walk away with a draft entity model either way.