Stride engineers partner with your team in a working session to instrument cost-per-outcome visibility, separate the AI spend that creates value from the spend that is waste, and find the surfaces worth optimizing first. No slide decks. No sales pitch. Just senior engineers building with you.
Stride implements model routing and tiering so affordable models handle routine tasks and premium models handle complexity. Typical result: 40 to 60% cost reduction on routed surfaces with no measurable quality loss.
Stride built a model-switching AI agent for 73V that automates SMS-based patient inquiries. Confidence-based routing directs 85 to 87% of queries to high-speed models while escalating complex clinical cases to human clinicians. $360K in documented annual savings.
Stride instruments per-feature token attribution and establishes cost-per-outcome metrics inside the first two weeks, so your team sees what value each surface produces relative to its cost, turned into a prioritized backlog.
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A working session with a senior Stride AI engineer who has shipped cost-instrumented agentic systems in production.
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Cost-per-outcome visibility for your 2 to 3 highest-spend AI surfaces, grounded in your actual systems and token data.
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A candid read on where you are overspending, including which surfaces can be optimized now and what needs eval infrastructure first.
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A follow-up summary with a prioritized optimization backlog and projected savings. Yours to keep regardless of whether you engage Stride.
No commitment. No slide deck. No sales pitch. Just a technical working session with engineers who build and optimize agents for a living.
Stride engineers embedded with our team and built a working AI agent in weeks, not months. The system is in production handling thousands of patient interactions, and it paid for itself within 90 days.