The buy-versus-build line has moved. Workflow tooling that once required eighteen months and a licence can now be built in weeks, and the enterprises acting on that are rebuilding the software layer around how their business actually runs rather than configuring someone else's product around it.
Product engineers, software and AI engineers, business process engineers and industrial engineers work together, because process redesign without build authority produces a recommendation, and building without process authority produces a faster version of work that should not exist.
Systems of record stay where they are. Searce works the layer above them: the workflows, the internal tooling, the orchestration, and the custom systems that carry competitive advantage.
Name one process that should work dramatically better than it does.
Process re-engineering and work redesign, with the build authority to make it real. Process intelligence and dependency mapping to find where the work actually breaks, then agentic workflow engineering to rebuild it - not a recommendation deck, a running system.
Which system are you working around rather than working with?
Enterprise systems rebuild at the workflow layer replacing legacy and SaaS where configuration has become contortion. Includes systems consolidation and rationalisation, and application and product engineering for the custom systems that carry competitive advantage.
Is there a process you would hand to someone else if they could prove they would improve it?
Searce takes operational ownership of a process and rebuilds it while running it. Improvement is measured, not promised. The process comes back better than it left, with the economics to show it.
What would you do differently if you could prove which revenue came from the AI?
AI engineered into revenue and customer workflows with attribution built in from the start, so every system answers not just "did it run" but "what did it earn."
AI Outcome Engineering redesigns workflows, decisions, and operations around AI to create measurable business outcomes.
From manual financial operations to continuous, AI-assisted decision-making.
Redesign how finance teams plan, analyze, reconcile, report, and make decisions by embedding AI into high-volume workflows and critical financial processes.
From fragmented people processes to intelligent workforce operations.
Reimagine how employees and HR teams access knowledge, complete tasks, manage talent, and navigate everyday workforce processes.
From reactive IT operations to autonomous, resilient systems.
Embed AI across IT service management, engineering, support, and operations to resolve issues faster and reduce repetitive work.
From disconnected marketing activities to intelligent customer engagement.
Connect customer intelligence, content, campaigns, and marketing operations with AI, helping teams move from insight to execution faster.
From manual legal workflows to AI-enabled legal operations.
Bring AI into contracts, research, compliance, knowledge, and review workflows to reduce repetitive work and accelerate legal operations.
Reimagine the processes at the heart of your industry.
Apply AI Outcome Engineering to the mission-critical workflows unique to your business, from patient care and claims to manufacturing, commerce, logistics, and other industry-specific operations.
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Five processes re-engineered and rebuilt, each measured against the baseline it started from.
“This takes forty-one steps and four teams.”
wasClaims journey from 41 steps to 12.
“Underwriting decisions take hours we do not have.”
was6.5 hours to 22 minutes.
“Approvals sit in a queue nobody owns.”
83% of prior authorizations touchless.
“The close takes so long the numbers are stale.”
was11 days to 2.
“Exceptions eat the team’s week.”
Freight exception handling 8x faster.
AI-native engineering with evaluation suites, regression harnesses and human review at every gate.
A named operating owner
Documented maintenance economics
A defined exit path