LLM Semantic Caching Services for Your Business
LLM semantic caching recognises when a new question means the same as an old one and returns the stored answer without calling the model. Omeiro builds the cache with GPTCache and Redis, tunes how similar is similar enough and adds rules for expiry.
How LLM semantic caching works, step by step
A made-up example of one run, from start to finish. Each step is logged so you can see what happened.
- Your documents are loaded
Files are split, indexed and kept in your own storage.
- A question comes in
The system finds the parts of your documents that match.
- The model answers from them
Answers point back to the source so people can check.
- People review the edge cases
We agree what happens when no good answer is found.
Sample Made-up names, data and steps to show how a run is logged. Your steps, tools and rules follow your business.
What you get with LLM semantic caching
Vector similarity caching intercepting recurring enterprise queries using GPTCache and Redis. Slashing API token expenditure by 40–60% with sub-10ms response times for cached prompts.
Basic Package
Redis semantic cache for 1 app endpoint, similarity threshold tuning. 3-day delivery, 1 round + 30-day fixes.
Standard Package
Up to 4 endpoints, TTL; invalidation rules, hit-rate stats, docs. 6-day delivery, 1 round + 30-day fixes.
Premium Package
Multi-tenant cache, savings dashboard, load test, 30 days support. 10-day delivery, 1 round + 60-day fixes.
Clear brief first
We confirm what you need before work starts, so the scope is clear on both sides.
Revisions listed
Each package shows its revision rounds. A round is one list of changes sent together.
Yours once paid
Copyright of the final work passes to you once the order is paid in full.
Third-party tools, API usage and hosting are billed to your own accounts, so the setup stays with your business.
How our LLM semantic caching works
Study repeat traffic
We check how often questions recur.
Pick the threshold
Similarity is tuned so wrong matches are rare.
Add expiry
Rules decide when answers go stale.
Measure savings
Hit rates show what was saved.
LLM semantic caching: where it works and where it is risky
Caching suits repetitive, stable questions. LLM semantic caching works well for FAQs, policy lookups and public product information, where many users ask the same thing in different words and the answer rarely changes. It is riskier for personalised or time-sensitive queries, where a stored reply may be wrong for the next user. Before ordering, sample your traffic and sort it into repeatable questions and unique ones, so we know where the cache belongs.
The similarity threshold is a safety setting. Too loose, and a question about cancelling an order may return an answer about refunds; too strict, and the cache rarely hits. LLM semantic caching should be tuned on your real queries, with a review of near-miss matches. Set expiry so changed prices or policies do not linger, and keep customer-specific data out of shared entries. Tell us your traffic mix and freshness rules so the caching strategy fits.
In short
- Delivery in 3 to 10 days, by package.
- Fixed price, shown before you order.
- Teams whose users ask the same support questions in many words.
- Finance leads watching tokens burn on repeat queries.
- Copyright yours after full payment.
LLM Semantic Caching: common questions
How much does LLM semantic caching cost?
Prices are fixed and shown by package on our LLM Semantic Caching pricing page, so you see the full price before you order. You can also ask for a custom quote.
How much does LLM semantic caching cost?
Prices are fixed and shown by package on our LLM Semantic Caching pricing page, so you see the full price before you order. You can also ask for a custom quote.
How long does reduce LLM API caching take?
Delivery depends on the package: Basic 3-day delivery; Standard 6-day delivery; Premium 10-day delivery.
What is included in the Basic Package?
The Basic Package includes: Redis semantic cache for 1 app endpoint, similarity threshold tuning. Higher packages add more scope, revisions and support.
Can I get a custom AI query caching package?
Yes. If none of the packages fits, use the custom package form on our pricing page to describe what you need, and our team sends you a fixed price.
Could the cache return a wrong answer?
If the threshold is too loose. Tuning aims to prevent it.
How long are answers kept?
TTL rules from Standard decide.
Is it safe for multiple customers?
Premium offers a multi-tenant cache.
What is the difference between semantic caching and exact-match caching?
Exact-match caching only returns a stored answer when the text is identical. Semantic caching also catches differently worded questions that mean the same thing, so it hits far more often.
Who owns the final work?
Copyright of the final work passes to you once the order is paid in full. Paid fonts, stock files or licences, if used, are licensed in your name.
Ready to start your LLM semantic caching?
Compare the packages and pick the one that fits. Not sure which? Write to us and we will help you choose.