Build production-ready, resilient agents. Six new capabilities across retrieval, memory, routing, and messaging.
AI COST OPTIMIZATION
Token caps and usage limits aren’t the answer for runaway spend.
Burning tokens on repeat answers
Every unnecessary LLM call costs money. Generating new answers to repeat questions, redundant requests, or because an agent forgot a conversation burns tokens without adding value.
Smarter AI spend relies on reusing relevant responses.
Losing time means losing money
Forgetful agents make customers and employees repeat themselves. Each extra prompt adds model calls and delays, resulting in bad UX that frustrates employees, loses customers, and costs more tokens.
Agents have to carry relevant context forward to control costs.
Spending too much on expensive RAM
Datasets don’t stop growing, but infrastructure budgets do. RAM is ideal for hot data, but SSD can handle the rest for less money.
Invest in infra that automatically moves data between RAM and SSD as access patterns change.
Usage limits and token caps or switching to cheaper models are the obvious answers for rising AI costs.
But these choices come at the sacrifice of performance and usability. The bill goes down, yet you get less value from AI investment.
The answer to expensive AI isn't less AI.
It's less expensive AI.
AI spending is growing, but the return isn’t always clear.
Join Redis CEO Rowan Trollope and CFO Tony Tiscornia to explore how leaders are thinking about AI efficiency without slowing innovation.
Learn how to focus investment, reduce waste, and turn productivity gains into measurable business value.
Reuse responses for semantically similar requests instead of paying to generate the same answers again and again.
Make every agent interaction count with better memory and context to give users accurate, useful answers without unnecessary back-and-forth.
Keep hot data in RAM and warm data on SSDs and scale up and down as needed to make storing large datasets cost effective.
Our voice app for patient care gets a lot of specific treatment questions, so it has to be absolutely accurate, and that's what Agent Playbooks does. I was worried about LLM costs for high usage, but with Agent Playbooks, we're getting a 70% cache hit rate, which saves 70% of our LLM spend. On top of that, it’s 4X faster, which makes a huge difference for real-time patient interactions.
Find out where tokens, memory, and infrastructure are eating your budget.
