AI Cost & Performance Optimization
Inference Engineering
Your AI works. Now it needs to cost less to run. We optimise how your models are selected, called and served so you can reduce the cost and latency of AI workloads without compromising the quality your users expect.
Most teams are overpaying somewhere: the wrong model for the task, prompts carrying more tokens than they need, or repeated calls that never had to happen twice.
Financial Services
Retail & E-Commerce
Education
Core Capabilities
Inference is what happens every time your AI actually runs, and it is where the bill accumulates. We work on the layer between your application and the model, so you keep your product exactly as it is and pay less for it.
Model selection and routing
Prompt and token efficiency
Caching and request deduplication
Batching and throughput tuning
Quantization and self-hosted serving
Cost monitoring and spend visibility
Industry Solutions
Inference optimisation for teams where AI cost and response time directly affect the business. The same work applies to SaaS, healthcare and any team running AI in production, so ask us about your stack.
Financial Services
Control cost without loosening controls
Route routine checks to smaller models and reserve larger ones for judgment calls
Cut token waste in document and transaction processing at volume
Improve response times in customer-facing flows
Keep data handling and deployment aligned to your compliance requirements
Retail/Ecommerce
Handle peak demand without the peak bill
Cache repeated product, search and support responses
Keep costs predictable through seasonal traffic spikes
Reduce latency in on-site assistants and recommendations
Scale to more users on the same infrastructure
Education Technology
Serve more learners per pound spent
Match model choice to task, from simple grading to open feedback
Batch high-volume, non-urgent workloads to cut unit cost
Keep interactive tutoring responsive during busy periods
Support growth in usage without a matching rise in spend
What You Gain
Lower cost per request, with the quality and performance your product depends on
Lower cost per request
Reduce spend while maintaining the quality your application requires
Faster responses
Reduce latency in user-facing flows
More headroom to scale
Serve more users on the same budget
Clear visibility of spend
Know what is costing what, and why
How We Deliver
We start by measuring, so every change is backed by a number
1
Assessment
Measure current cost, latency and usage
2
Opportunity Analysis
Identify where spend is avoidable
3
Implementation
Apply changes and validate cost, latency and output quality
4
Ongoing Optimisation
Monitor spend and tune as usage grows
Frequently Asked Questions
Common Questions About Inference Engineering
Answers to what teams usually ask before optimising their AI spend
Inference is the process of running a trained AI model to generate an output from an input. In production, it becomes a recurring cost that generally grows with usage, unlike the one-time or periodic cost of training.
We benchmark output quality before and after optimization and set quality thresholds appropriate to your application. If an optimization causes unacceptable degradation, we adjust or revert it.
Usually not. Most of the work happens in how models are called, cached and routed, which sits alongside your application rather than inside a rebuild.
It depends entirely on your current setup. Teams that have never reviewed model choice or prompt size tend to have the most room. The assessment gives you a figure before you commit to anything.
Both. We work with providers such as OpenAI, Anthropic and Google, and with open models you run yourself. Often the answer is a mix of the two.
The bigger your volume, the bigger the saving, but smaller teams benefit from getting the architecture right early rather than rebuilding once costs become painful.
With an assessment of what you are running today, what it costs and where the waste is. You get the findings and a recommendation before any changes are made.
Ready to Reduce the Cost of Running Your AI?
We help teams keep the AI product they have built and pay considerably less to operate it.
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