Imagine how much you could get done if you had proper AI working for you at its full potential.
Every prompt-writer on your team becomes an on-demand AI analyst. StarMynd ABI delivers AI-ready business data to your isolated GCP project. You own the data. We run the pipeline.
AI is powerful. But AI without your accurate, well-structured business data can never be the AI you need it to be. AI + your business data = AI super powers for you and your team.
Every person on your team who can write a prompt to Claude or ChatGPT now has the power of an on-demand AI data analyst. They can ask "why did revenue dip last Tuesday," they get an answer grounded in your actual business data, with the receipts. They can build reports. They can make decisions. They can deploy or refine marketing workflows themselves.
Your engineering team does not have to staff a data analyst. Your marketing analysts do not have to learn SQL. Your CMO does not have to wait for the weekly dashboard refresh. Anyone on your team who can describe what they want in plain English gets the answer.
This is what AI-first marketing actually feels like inside the org. Most companies cannot get here because their data is not ready for AI. Ours is.
Three layers of the same problem most DTC teams have not named yet.
BI data is designed for humans. Weekly refreshes, cryptic column names, three-step pivots to answer a simple question. AI tools need joined, plain-English schemas refreshed daily and queryable on demand. None of your spreadsheets, dashboards, or cryptic data warehouses work when Claude needs to answer "why is our subscriber churn higher this month than last."
You have ChatGPT subscriptions. You have Claude Code installs. The AI tools work. The team is ready. The blocker is data. Every prompt that should land an answer lands a "I need more context" instead, because there is no clean, joined, AI-ready source of truth to point Claude at.
The future where every team member is an AI-powered analyst requires data infrastructure built for AI, not retrofitted from BI. Most companies have not built that yet. The few that have are pulling ahead. The teams who win the next two years are the teams whose data is AI-ready by month one.
The business data your CFO and your BI tool care about is not the same as the business data your AI tools need. ABI builds the AI-ready half.
The distinction matters. We want to be clear about it.
For most teams, paying $895 a month for ABI to keep their data AI-ready is cheaper than staffing a data engineer.
Seven components. Standalone market values are the reference cost if you built or staffed the equivalent yourself.
| Component | What you get | Standalone value |
|---|---|---|
| Clean unified business data, AI-ready | Shopify + Klaviyo + Meta + Google + Amazon + accounting, in BI-grade fact tables, refreshed daily | $20,000 to $40,000 of internal engineering build |
| Plain-English column names + joinable schemas | Designed for AI tools to query, not for humans to pivot | Distinct from default BI builds |
| MCP and tool-config integration | Claude Code, Codex, Cowork wired to your fact tables on day one. Every prompt-writer becomes an AI analyst. | $5,000 to $10,000 of integration work |
| Read-only data delivery by default | Read access by default; writes require explicit setup. CTO-friendly security posture built in. | Security posture included |
| Isolated GCP project per company | No data comingling. No shared datasets. Migration is mechanical, not architectural. | $2,000 to $5,000 of setup |
| Pipeline maintenance included | We adapt as Shopify, Klaviyo, Meta change their APIs. You never fix a broken integration. | $500 to $1,500 per month if staffed |
| Skool community access for your tech team | Implementation tips, peer learning, prompt patterns from other ABI customers | $49 per month per team member |
Each step is something your team can see. Each step earns the next one.
We map your stack, your AI use cases, and your team's capacity. We tell you on the call whether ABI fits before you onboard. No commitment, no procurement, no fees.
You provision a fresh GCP project under your company (we walk you through it). We provision the pipeline inside it. You hand us OAuth tokens for your sources. Your AI tools (Claude Code, Codex, Cowork) get configured to query the AI-ready data once it lands.
We adapt as Shopify, Klaviyo, and Meta change their APIs. New sources added. Schemas hardened. As a founding customer, you have direct input into the roadmap, and your requests get prioritized.
The $895 base covers a starter integration footprint, typically Shopify + Klaviyo + Meta + Google + Amazon + accounting. Pricing scales with the number of data sources you connect over time. As you add custom systems, regional accounts, secondary platforms, or new ad networks, pricing scales accordingly. Founding customers lock in their per-source rate.
Onboarding fee included for the first wave of private-beta customers. Future cohorts to be determined. Free scoping call upfront. If your stack is not a fit, we tell you on the call before you onboard. Cancel anytime during private beta. Your data stays in your GCP project either way.
ABI gives you the data half of the AI super powers. AI Architect is the team of two that helps you build the AI workflows on top. Most Architect engagements include ABI as the foundation. Both are required for the full Elena-shape engagement.
You can also start with ABI alone if your team has the capacity to build the AI workflows themselves. Many teams do. You can layer in Architect later if you want team-of-two delivery.
$895/mo starting
The data foundation. Scales with data sources connected.
$5,000 setup + $5,000/mo per department
Done with you delivery on top of the ABI foundation. Combined Elena-shape engagement around $15,895/mo.
See the AI Architect page for the team-of-two service and the per-department recurring model.
Without AI-ready data, your AI tools are stuck. With it, every prompt-writer becomes an analyst.
Your engineers build connectors instead of doing engineering work. Your marketing analysts build dashboards instead of doing analysis. Every Claude prompt that should land an answer lands "I need more context" instead, because there is no clean joined source of truth to point at.
The teams who lose the next two years are still wiring connectors in quarter four. The window to be AI-first closes around them.
Your CMO asks Claude why subscriber retention dropped, gets an answer with receipts. Your performance marketer asks Claude to flag channels with cost-per-acquisition drift, gets a workflow that flags them automatically going forward.
Your team ships more AI workflows in three months than your competitors ship in a year. You become the team other DTC teams cite when they are explaining what AI-ready looks like.
Founding customers lock in $895/month starting and retain their per-source rate when public pricing launches late 2026. The list is the path into private beta.
Join the founding-customer list for StarMynd ABI.
You will hear back from Andrew within one business day with a private beta scoping link and next steps.