A studio— for AWS account managers
I research them. I find the AI use case adjacent to what their CIO already worries about. I build a tailored artifact on AWS. I walk into the meeting with you. Founder-led. Native to your stack.
01 — The problem you actually have
Then six months pass — and nothing ships.
The blocker isn't budget. Most of your customers can find a few hundred thousand euros for a pilot. The blocker isn't appetite — every CIO has been told they need an AI strategy by Friday.
The blocker is the absence of a story they can show their board that says "this is us, doing this, on AWS, by Q3." Until that story exists, the meeting after the meeting after the meeting is the only thing happening.
02 — The pattern
Each phase has a tight deliverable. The whole sprint is one customer, one artifact, one meeting.
Read everything public about the customer — annual report, regulatory posture, recent press, hiring pattern, stalled initiatives. Map their org chart, their adjacent AWS spend, the questions their CIO has been asked twice this year.
Find the three AI use cases that already feel obvious to them — adjacent to their existing pain, mapped to AWS services, costed monthly, time-to-ship-able. Each one a sentence their CIO can repeat to the board.
Ship a tailored artifact. A bilingual website (like the medical-manufacturing case below). A working PoC against their data. A demo app with their branding. Whatever fits the meeting medium and the customer's culture.
I walk into the meeting with you. Present, answer the technical questions a salesperson can't, leave the customer with something they can forward to their board the same evening. Then we hand off — or repeat for the next customer.
03 — Live example
A regulated medical manufacturer in DACH. AWS account manager brought the relationship. I shipped this in five days — bilingual site, AWS-native architecture diagram, governance section, three customer-shaped use cases. Full URL on request.
Six departments mapped to twelve AWS services. A five-layer agentic architecture diagram. Three concrete use cases adjacent to their regulatory reality (clinical/regulatory intelligence, multilingual compliance docs, RFP response crew). A short governance section answering the six audit questions any CISO eventually asks. All on a Bedrock + SageMaker + Step Functions stack, costed at ~$385/month.
04 — What this looks like for your customers
Sketches, not promises. Each is a 10-day sprint. Each lands in a meeting with an artifact a CIO can forward.
05 — How we'd actually work together
No agency overhead. No three-month onboarding. No SOW thicker than the artifact. The deal is small and clear.
06 — Why this lands for AWS, not just for the customer
Every artifact I ship defaults to AWS-native services. Every "yes" your customer gives is a workload that lands on Bedrock, SageMaker, Step Functions, Neptune. The acceleration is yours, too.
Customers who would have stalled six months sign a pilot in two weeks. The artifact is the unblock — they now have something concrete to defend internally.
Bedrock for inference, SageMaker for fine-tunes, Step Functions for orchestration, Neptune for graphs. Real workloads on day one, not slides about hypothetical workloads later.
Your hours stay where they create value: customer conversations, strategic positioning, deal architecture. I handle the artifact, the technical depth, and the meeting craft.
Different conversation than a partner-network firm. A founder showing up, answering technical questions live, with their own scars from running a company on AWS — that's a posture customers respond to.
07 — How to start
Email ed@vexpertai.com with one line per field: Customer · Industry · AWS region · Meeting date · What's been said so far. The two-week clock starts when we agree the brief. AWS account managers, partner managers, and startup-team folks all welcome — I work with whoever owns the relationship.