THRIFT-01

AI Cost Optimization

Find out exactly where your LLM spend is going — and how to cut it 30-60% without losing capability.

$8,000report5 days

[ WHO IS THIS FOR ]

VP Engineering, CTO, or finance-adjacent technical leader spending $5K–$100K per month on LLM APIs and AI infrastructure.

You need this when:

LLM costs are growing faster than revenue
Finance is pushing back on AI infrastructure spend
Preparing a board update on AI unit economics
Scaling fast and need to understand cost trajectory
Recent spike in API costs with unclear cause
AI vendor contract expiring — need to evaluate switching costs

[ ROI FRAME ]

RETURN ON INVESTMENT

Clients with $20K/month LLM spend routinely find 30-50% savings — $6K–$10K/month in recovered costs. This report pays for itself within 2 weeks of implementing the first recommendation.

WHAT YOU GET

20-30 page cost optimization report
Spend analysis by feature, model, and usage pattern
Ranked optimization recommendations with projected savings
Implementation playbook for each recommendation
Model comparison matrix (cost vs. performance)
Caching and batching strategy recommendations
Vendor switching cost analysis (if evaluating alternatives)

WHAT YOU PROVIDE

90 days of LLM API usage logs (any major provider)
Infrastructure cost breakdown by service
AI-powered features and their usage volume
Current model selection rationale
Existing optimization efforts (if any)

[ ALTERNATIVES ]

Internal engineering review (slow, lacks benchmark data)
LLM provider optimization guides (generic, not business-specific)
Cost optimization consultant ($15K–$40K for similar scope)
Do nothing (costs compound monthly)