First real users, and numbers that are not yours
A narrow slice of the product, built with your team or a partner, put in front of people who did not build it. The output is not a demo. It is measured use.
- 1–3 months
- Built with your team
- AWS PoC funding up to €10,000
- Remote or on-site
The rung where opinion stops mattering
Up to here, every judgement has been made by people close to the project. An MVP hands the question to users, on a real journey, doing real work.
The scope is deliberately narrow: one journey, end to end, rather than every feature at partial depth. Breadth is what turns a three-month MVP into a nine-month one that still proves nothing.
This is also the first rung where operations become real. Something has to be monitored, something has to be on call, and someone has to own the cost line[5].
Check AWS funding before you pay.
Many AI proofs of concept and cloud migrations qualify for AWS funding: credits for the AWS usage and, in some partner programmes, funds for the delivery work. What applies depends on the project, the programme and the AWS account team. I check it in the Idea Call, and the workshop results are written so they can go straight into an application.
Proof of concept
For a prototype on AWS with a clear path to production.
Migration
For larger cloud moves, planned in phases.
Evidence, not enthusiasm
Usually built with your team, or with specialists from my network where capacity is short.
A narrow journey, end to endIncluded
One complete path through the product for one group of users, rather than every feature half-built.
Measured adoptionIncluded
Who used it, how often, where they dropped out, and what it cost per request to serve them.
A production roadmapOptional
What has to change for this to be run properly: security, operations, scaling, in weeks rather than quarters.
The funding caseOptional
Results written up in the form an AWS proof-of-concept funding request expects[4].
Real patterns, documented in the open.
Typical candidates at this stage, each documented on ai-solutions.wiki with architecture and trade-offs.
Intelligent Document Processing with AI
A practical architecture for extracting structured data from invoices, contracts, and forms: combining OCR, classification, and LLM-based extraction.
Read on ai-solutions.wiki →Customer supportAI Knowledge Base Automation for Customer Support
Automated knowledge base creation, maintenance, and optimization using AI to keep support content accurate, comprehensive, and discoverable.
Read on ai-solutions.wiki →InsuranceAI Policy Document Processing for Insurance
Automated extraction, classification, and analysis of insurance policy documents, endorsements, and regulatory filings using NLP and document AI.
Read on ai-solutions.wiki →Most projects should stop here
A successful MVP does not automatically justify a product. It justifies a decision, taken with numbers, about whether the full thing is worth building and operating for years.
If the answer is yes, the last rung is the expensive one, and it is much less about AI than people expect.
Ideas
Who needs this most?
The idea said out loud, and who it is actually for. Out: a shortlist
Free 30-min callClarity
Is the idea clear?
Written so anyone in the room can repeat it back without you. Out: one page
Concept
Is it technically working?
The idea shown, not described: data, layer and approach chosen. Out: a concept
Cloud demo
Does it survive contact?
Something real to click, running in the cloud. Out: a demo you can try
2–24 hoursMVP / POC
Do users adopt it?
First public customers on a real user journey, built with your team or a partner. Out: measured use
1–3 monthsFunctional product
Ready to scale?
Market-ready, scaled and operated, with someone on call. Out: a product
3–12 months+Ideas found on the way get parked. They stay in the discussion and out of the build, so the current step keeps its scope and nothing is quietly forgotten.
The full ladder. Every rung answers one question and leaves something people can look at or try. Each stage links to its own page.Source: Linda Mohamed, AI Use Cases Workshop deck, 2026
Where the facts come from.
Prices, service names and limits change. The linked official pages are the reference; figures on this page were checked in September 2026.
- AWS Well-Architected Framework
- AWS Pricing Calculator
- AWS: Amazon Bedrock pricing
- ai-solutions.wiki: From AI proof of concept to production
- ai-solutions.wiki: Total cost of ownership for AI
- ai-solutions.wiki: Build vs buy for AI
- ai-solutions.wiki: AWS funding for proofs of concept
- Regulation (EU) 2024/1689, the EU AI Act
- Documenting architecture decisions (ADR), Michael Nygard
Start with one conversation.
30 minutes to look at your idea, your data and the right starting point. Or book 15 minutes if you only have a question.
- Which journey the MVP should cover
- What adoption would have to look like
- Who would operate it
- Whether AWS funding could apply
Vienna, Austria · remote across Europe · [email protected]
