AI-Driven Product Discovery
Validate scope, architecture, and ROI before committing to a full build — from hypothesis to a working proof-of-concept with a costed roadmap in 1–2 weeks.
The business problem
The most expensive AI mistake is building the wrong thing well. Teams commit six-figure budgets to ideas that were never validated against their data, their users, or a realistic architecture — and discover the gaps only after the build.
Discovery de-risks that decision. In one to two weeks you learn whether the use case is feasible, what it will actually cost, and what the fastest path to value looks like.
What Softoryze delivers
- A prioritised map of AI use cases scored by value and feasibility
- A data audit that tells you honestly whether your data can support the idea
- A working proof-of-concept that proves the hardest part, not a slide deck
- A costed architecture and phased delivery roadmap you can act on
Capabilities
- Use-case discovery workshops and opportunity sizing
- Data readiness and quality assessment
- Rapid prototyping of the highest-risk component
- Architecture and integration planning
- Cost, timeline, and ROI modelling
What you get — six deliverables, all yours to keep
Evaluation set (your AI spec)
A dataset of real inputs paired with reference outputs and assertions — easy, edge, and adversarial cases. The spec your AI must meet, reusable across model and vendor changes.
Architecture proposal
A working architecture diagram with the simplest viable design: data flow, tool inventory, failure modes, and written rationale for every non-obvious choice. Multi-agent only where the eval forces it.
Cost-per-request model
The actual dollar cost at 1x, 10x, and 100x your projected traffic — token math, cache assumptions, routing strategy, and the cost levers you can pull as the bill grows.
Build estimate with confidence intervals
An engineer-month estimate broken down by component, with stated assumptions, P50 and P90 timelines, and where the risk lives.
Go / no-go memo
A written recommendation — build, shelve, or restart — in three paragraphs your board can read in five minutes. We'll recommend 'don't build this' if the numbers say so.
Risk & compliance register
For regulated workloads: data-residency posture, audit-logging design, fairness and drift considerations, and the policy gates that need deterministic code instead of prompts.
Tech stack
Eval & testing
Models
Frameworks
Retrieval
Don't see the tech stack you're looking for? Our team works across custom requirements and stacks — contact us and let's find the right fit.
Let's chatHow we approach it
- 01
Frame
We align on the business outcome you're targeting and the assumptions that must be true for it to work.
- 02
Audit
We assess your data and systems to determine feasibility before any code is written.
- 03
Prototype
We build a focused proof-of-concept that tests the riskiest assumption end to end.
- 04
Roadmap
You leave with a costed architecture, a phased plan, and a clear go/no-go decision.
“Manual booking coordination was breaking our operations. Softoryze rebuilt the process — our team moves faster, client communication is seamless, and scaling finally feels possible.”
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Let's scope your project.
Talk to a senior engineer about your requirements — no sales layer, just a clear, honest conversation about what it takes to build it well.