One domain. Two trusted data products. Three months.
In 90 days, we build two trusted AI Data Products with your team and leave you with the capability to build the next ten.
Domain, with named stewards and a leader who owns the outcome.
Data products, packaged end to end and ready for AI.
Months, from scope to certified and published.
Sound familiar?
"We bought a catalog. I could not tell you if anyone opens it."
"Three teams rebuilt the same report because none of them found the first one."
"The one analyst who understands that table is leaving in March."
"The AI pilot stalled because we couldn't agree on what data readiness looks like."
None of these are tooling problems. All of them are what happens when nobody owns the answer.
The inventory spiral.
A tool is only part of the solution. Treated as a quick fix, it gets ignored.
- 01
Leadership buys a catalog.
- 02
Stewards are asked to document everything.
- 03
Documenting feels like a chore with no payoff.
- 04
Coverage goes wide but stays shallow.
- 05
Nobody gets what they need.
- 06
And nobody opens it again.
It's not about cataloging. It's about building products.
A data product is a trusted, reusable asset built with purpose. Here is what makes data ready for AI.
Quality rules, lineage, freshness.
Can I believe it?
Definitions, metrics, grain, synonyms, relationships.
What does it mean?
Caveats, known gotchas, decision rules, how people actually use it.
How do I act on this?
AI-ready data products in three months.
Domain
One domain, two to five teams, named stewards, and a leader who owns the outcome.
Products
Packaged end to end: definitions, CDEs, quality, semantics, classification, access, and evals.
Months
The catalog, the roles and the mechanisms get built because the products need them.
The marketplace, configured.
Discovery
Metadata standardized so people find and understand products relevant to them.
Trust
Lineage verified source to surface, quality rules monitored, failures alert a named owner.
Access
Classification applied, the request path linked, usage measured.
AI context
Definitions, verified queries and evals, served through the catalog's chat.
Packaged to be scalable across domains.
Operations, lean by design.
Named and clear
- Sponsor
- Enablement lead
- Coordinator
- Platform owner
- Business steward
- Technical steward
Thirty minutes a month
Five or six people. Alignment and direction for the new capability.
One session a week
One 45 minute domain session per week. Hands-on support for the stewards to build the products.
Built to last
- Documentation
- Change control
- Product nomination
- Feedback and issue log
- Resource onboarding
Easy to understand, easy to maintain.
Scalable AI product capability.
Scope
Domain and products selected. Roles named. Catalog connected and configured. Standards agreed and questions captured.
Curate
Stewards trained and documenting. Definitions ratified, CDEs profiled, quality rules live, evals tuned. Products assembled in the marketplace.
Launch
Products certified and published with an AI scorecard. Consumers trained, readout and roadmap created. You take ownership.
We don't do the reps for you. We run them with you so your team knows what good feels like.
Ready means all eight pass.
A product is ready when all eight components pass with confidence. Your program is ready when it's easy to meet the expectations for each one. Tap each one your best data product can claim today.
Most teams pass a few. The gaps are where the Quick Start begins.
Your catalog connects the stack. The Archetype Operating Model keeps it trusted.
Whichever data intelligence platform you run, it should know what you have, trace where it came from, and put definitions and policies next to the data. Archetype supplies the roles, rules, and rhythm around it to keep the outcomes reliable.
- Enterprise warehouse
- ERP and finance
- CRM and operations
- Files, APIs, pipelines
One place for what you know
- Catalog
- Lineage
- Glossary
- Policies
- Data quality
- AI agents
Centralized knowledge, available everywhere.
- BI and reporting
- Analysts and science
- AI and agents
- Compliance and audit
Owners, workflows, cadence.
Metadata, domains, tagging.
Training, playbooks, comms.
Adoption KPIs, roadmap.
Where we've done this.
Examiner AI on a governed semantic layer, with no PII exposure.
Analyst AI agent live in 6 weeks, recovering 80 hours a month.
Governed metric thread live on Snowflake, deployed as code.
Catalog stood up from scratch, with operating model and charter.
A second domain cheaper than the first.
Start on the right foot.
These five questions alone can get you started. Bring your answers to the call.
- 1What data gets the most questions?
- 2How much trust do you need in the answer?
- 3What happens if the answer is wrong?
- 4Who owns the answer when it is wrong?
- 5Does everyone agree what "good" looks like?
Book a 30 minute call.
Faster value. Stronger adoption. Lasting impact. Pick one domain and we'll walk through what your first two products look like.
Practical advisors. Hands-on builders.
Snowflake EliteSnowflake Elite Services Partner
Cortex CodeCortex Code Preferred Partner
Founded in Boston
Leaders do not just need answers. They need outcomes.
At Archetype, forward is not just a direction. It is a decision. We partner with leaders who are ready to move, with precision, with speed, and with purpose. We build with you, not at you.
Forward Ready.
Measurable · Strategic · Scalable · Actionable · This is consulting that activates