LLM and AI token cost optimisation
Reduce your LLM and AI token costs without losing quality
AI cost optimisation lowers what you pay to run large language models by reducing the tokens each request uses and sending each task to the cheapest model that can do it well. e-KHOOL audits your AI usage, applies prompt, caching and model-routing changes, and reports the cost per task before and after. Tria PLC cut its AI workflow cost by 35%.
AI implementations delivered for
Where AI spend usually goes
Most AI bills grow from a few avoidable patterns. The audit finds which ones apply to you, then ranks each fix by saving and quality risk.
- Long prompts: the same instructions and context resent with every call
- Oversized models: the largest model used for summaries and classification
- No caching: repeated questions and documents paid for again
- Runaway agents: loops and retries with no limit
- No visibility: no cost per task, team or workflow
How we reduce LLM costs
Six levers, each tested against your quality benchmarks before it goes live.
Prompt and context optimisation
Shorter prompts and smarter context retrieval send fewer tokens per request.
Model routing
Simple tasks go to smaller, cheaper models; complex tasks go to stronger ones.
Caching
Reuse answers and processed documents instead of paying for them again.
Agent guardrails
Limits on loops, retries and tool calls stop runaway spend.
Private model hosting
Move high-volume workloads to self-hosted models where it costs less than API pricing.
Cost monitoring
Dashboards showing cost per task, team and workflow, with alerts.
35% lower AI cost on Tria PLC's ERP workflow
Tria moved a manual ERP process onto AI agents on AIRA. e-KHOOL then ran its AI cost audit on that workflow and tuned how it uses AI, and its cost fell by 35%. Tria also rolled out eight AI agents for its teams.
35%Lower AI workflow cost after e-KHOOL optimisation
What we measure before and after
Every saving is reported against the same metrics, so you can see what changed and why.
| Metric | What it shows |
|---|---|
| Cost per task | What one completed request costs, the headline number |
| Tokens per request | How much prompt and context each call sends |
| Model mix | Share of calls going to small, mid-size and large models |
| Cache hit rate | How often repeated work is reused instead of paid for |
| Agent steps per task | Loops, retries and tool calls behind each result |
| Quality score | Answers checked against your benchmark, so savings never cost accuracy |
How the AI cost audit works
From usage review to a before/after report.
- 01
Usage review
We analyse your AI logs, invoices and top workflows.
Week 1
- 02
Savings plan
A ranked list of changes with the estimated saving and quality risk of each.
Week 1
- 03
Apply and test
Changes are made and tested against your quality benchmarks.
Weeks 2–3
- 04
Before/after report
Cost per task and quality measured before and after.
Report
Case studies from our AI implementations
Tria PLC cut its AI workflow cost by 35%.
AI cost optimisation FAQs
Why are LLM costs so high?
Most AI providers charge per token, so long prompts, large models used for simple tasks and repeated calls quickly multiply the bill.
How can I reduce LLM costs?
Shorten prompts, cache repeated work, route simple tasks to smaller models and set limits on agent loops. Measure cost per task so you know which change works.
Will cutting costs reduce answer quality?
Not if each change is tested against a quality benchmark before it goes live, which is part of every e-KHOOL audit.
How much can we save?
Results depend on your setup. e-KHOOL reduced Tria PLC's AI workflow cost by 35%. The audit estimates the saving for each of your workflows before any change is made.
Which AI providers do you work with?
Widely used commercial and open-weight models, plus e-KHOOL's own models.
Find out what your AI should cost
Share your current AI usage and we will show where your savings are. A solutions lead will reply within 1 business day.
- Savings estimated before any change
- Quality tested before go-live
- Or email sales@ekhool.com
Find out what your AI should cost
Share your current AI usage and we will show where your savings are.