Most AI pilots don't fail because the model is weak. They fail because the workflow, data, integration, controls and business case were never designed for production. We diagnose the pilot, decide what to kill, fix or scale, and turn the best one into a governed production workflow. Mach speed. Lily craft.
A demo proves it can work. Production proves it does — on real data, real users and real risk.
Industry research is consistent: a large share of AI and agentic projects are abandoned because of unclear business value, cost or inadequate controls. The model is rarely the problem. The gap is everything around it — messy data, brittle integrations, missing oversight and a business case no one stress-tested. Mach Lilies runs a focused audit, gives you an honest kill / fix / scale recommendation, and productionises the pilots that deserve it.
A focused audit that ends in a clear decision and, where it is justified, a path to production.
We pressure-test the value: what the pilot is meant to achieve, what it would really save, and whether that justifies production.
Where the pilot fits the actual process — and where it breaks against real handoffs, exceptions and edge cases.
An honest look at the data quality, sources, APIs, identity and permissions the pilot needs to work in production.
Where the pilot can go wrong, what that would cost, and which controls are non-negotiable before scale.
For the pilots worth saving: hardening the prototype into something robust enough for real use.
A fixed-scope rollout plan with architecture, monitoring and AgentOps controls — or a clear recommendation to stop.
Four movements from a stalled pilot to a clear decision — and, where it's earned, a path to production.
Understand what was built, why it stalled, and what it was really meant to achieve.
An honest, evidence-based recommendation — including the pilots you should stop.
Fix the data, integration and control gaps that kept it stuck in demo.
A fixed-scope rollout plan with governance, monitoring and ownership built in.
For leaders who invested in AI, saw a promising demo, and can't get it into reliable production.
We'll tell you to stop when stopping is right. A clear kill decision saves money too.
We've shipped systems that survive real users and real load — not demo-day theatre.
A short, fixed-scope audit, not an open-ended consulting retainer.
If it goes to production, it goes with controls, monitoring and an audit trail.
A clear kill / fix / scale decision — with an ROI model, a risk review and a production plan.
AI pilot rescue is a focused engagement to diagnose a stalled AI project and decide what to do with it. We audit the business case, data readiness, workflow fit and risks, then recommend whether to kill, fix or scale it — and, for the ones worth saving, produce a plan to take them to governed production.
Rarely because of the model. They stall on messy data, brittle integrations, missing human oversight, unclear value, and a business case no one stress-tested. Industry research attributes most cancellations to unclear value, cost and inadequate risk controls — all of which are fixable, or at least knowable early.
Yes, when that's the right answer. A clear, well-reasoned decision to kill a pilot frees budget and attention for the ones that will pay off. We'd rather give you an honest recommendation than bill you to scale something that shouldn't be.
It's deliberately short and fixed-scope — typically a focused audit measured in weeks, ending in a recommendation and, where justified, a production rollout plan.
A kill / fix / scale recommendation, an ROI model, a data and system readiness review, a risk and failure-mode review, and — for viable pilots — a production architecture and governance plan with fixed scope.
We can take it to production as an Agentic Operations engagement: hardening the system, building in AgentOps controls and monitoring, and operating it or handing it over to your team.
Tell us what you built, why it stalled, and what it was meant to achieve. We reply to every serious enquiry within one business day with an honest first view.
