We test feasibility and affordability of planned AI investmeent in a 4-6 weeks sprint, per use case, allowing you to make an informed decision before you committ to full-scale deployment.
A functional prototype using real data and working in real-world conditions – tangible and testable.
You will know whether the solution can be implemented technically, efficiently, and within budget.
We provide you with a clear view of feasible & affordable solution pathways.
Every technical, operational, and compliance risk will be identified, along with the corresponding derisking steps.
We build a lean, functional slice of the architecture (e.g., testing 100 legal contracts against a specific LLM) to prove accuracy benchmarks before designing the UI.
We calculate unit economics. If a prediction model costs $5 per query in API fees but only saves $2 in labor, we kill the project early.
A solution nobody uses is worthless. We test the prototype with real users to ensure the workflow feels natural, not intrusive.
Honest advice. If the tech isn't there yet, we tell you to wait. If it works, you get a green light backed by data, not gut feeling.
We protect organizations from committing capital to solutions that cannot be delivered, scaled, or justified in production. By stress-testing feasibility, cost, and operational risk upfront—and challenging assumptions before development—we reduce the likelihood of late-stage failure, reputational damage, and stalled initiatives. Our priority is clear: ensure that AI decisions are made deliberately, not reactively, and that every investment can be defended internally with evidence, not enthusiasm.
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Book a 30-minute discovery call to discuss your planned AI initiative, uncover hidden technical or cost risks, and determine whether the investment should move forward, pause, or stop—based on evidence, not optimism.