AI Token Cost Optimization

Stride engineers pair with your team to align AI spend with business outcomes. Every token visible, defensible, and tied to the value it creates.

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36% Savings
Realized on a $1M AI spend in a previous Stride engagement.
Stride engineers have been trusted by teams at

AI Cost Optimization in Production. Not in Slide Decks.

40-60%
Cost Reduction on Routed Surfaces

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.

$360K
Annual Savings

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.

2 Weeks
To Cost-per-Outcome Visibility

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.

What You Get

Cost-per-outcome visibility at the level of your current business reporting, within the first two weeks.

Validated cost reduction on optimized surfaces: savings you can quantify and defend.

Unit economics for AI features, plus eval and routing in production so your team can keep testing cheaper configurations after we leave.

Two Principal AI Engineers embed with your team for the engagement, in your standups and codebase daily, while a Stride Partner checks in weekly to keep priorities aligned with engineering leadership.

Duration starts at 8 to 12 weeks depending on the surfaces in scope. Cadence is a weekly priorities review and fortnightly written progress updates with quantified impact.

Frequently Asked Questions

What is AI token cost optimization?

An engagement where Stride engineers instrument cost-per-outcome visibility, then optimize model routing and prompts so AI spend stays aligned with the value it creates. Cheaper models handle routine tasks while premium models are reserved for complexity, typically producing 40 to 60% cost reduction on optimized surfaces with no measurable loss in output quality.

How much can we expect to save?

Results vary by surface, but Stride typically sees 40 to 60% cost reduction on routed surfaces. In one case, a model-switching AI agent built for 73V Healthcare directs 85 to 87% of SMS-based patient inquiries to high-speed models and escalates complex clinical cases to human clinicians, producing $360K in documented annual savings.

How long does the engagement take and what's included?

Engagements run 8 to 12 weeks depending on how many surfaces are in scope. Two Principal AI Engineers embed directly with your team, in your standups and codebase daily, while a Stride Partner checks in weekly. You get cost-per-outcome visibility within the first two weeks, validated and quantifiable cost reductions, and the unit economics, evals, and routing infrastructure your team can keep using after the engagement ends.

How quickly will we see results?

Stride instruments per-feature token attribution and establishes cost-per-outcome metrics within the first two weeks, turned into a prioritized backlog. Cadence throughout includes a weekly priorities review and fortnightly written progress updates with quantified impact.

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.

— VP of Operations
73V Healthcare

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