Two weeks in. A build-ready blueprint out.
The AI Opportunity Sprint is a brief engagement with a well-defined scope; it involves auditing your data and systems, ranking your AI opportunities according to their real-world value and feasibility, and then providing you with a technical specification that is ready for implementation. Even if you choose to build somewhere else, you will still get the answer.
The sprint exists for three situations.
While leadership would like for AI to be included on the roadmap, no one has yet ranked the various use cases based on your actual data and systems.
There are five teams, five pilots, and no shared standard for deciding which of them should get engineering time first.
You want to see the architectural design, the plan, and the genuine risks before agreeing to have the building carried out.
Deliverables, not decks.
Ranked use cases
The AI opportunities have been evaluated in terms of value, feasibility, and data readiness, including the honest 'not yet' entries.
A build-ready technical specification
The architecture, the integrations, the edge cases, and the acceptance criteria relating to the top use case — this is the same specification that our own build stage begins with.
Architecture & integration map
The way it integrates with your current systems and cloud services — whether those are GCP or AWS — down to the specific integration points.
A delivery plan
The key milestones, the structure of the team, and a realistic timeline — along with the risks we would want to keep an eye on, stated clearly.
An engineering read-out
A working session with the engineers who carried out the analysis — your questions answered by the people who will build it.
Yours either way
You can keep the blueprint. Whether you decide to go ahead and build with us, build it yourself, or put it aside, you'll have your final decision.
Ten working days, roughly.
Structured sessions covering your goals, systems, data, and constraints — along with access to what we need in order to look under the hood.
We compare the use cases with your reality, test their feasibility under pressure, and prepare the specification for the most suitable candidate.
You will go over the entire blueprint with our engineers, question anything that seems doubtful to you, and then leave with the final documents along with a clear next step.
Typical duration: 1–2 weeks · Fixed scope, agreed upfront
The sprint is Stage 1 of the SoftmaxAI Method, productized.
A written specification that has been approved by the client prior to any coding taking place — covering the architecture, the edge cases, and the acceptance criteria.
The engineers arrange for the AI agents to carry out the specification in parallel, taking weeks rather than quarters.
The evaluations, tests, and security checks are carried out together with the build, and humans examine every decision that is important.
The system has been deployed to your GCP or AWS, complete with monitoring, production evaluations, and retraining loops.
Fair questions.
What exactly do we walk away with?
What do you need from us?
What if the sprint concludes AI isn't the right answer?
Are we committed to building with SoftmaxAI afterwards?
Ready to stop debating and start speccing?
You can book the sprint, or instead have a free 30-minute call to make sure it's a good match — in either case you'll speak to an engineer.