AI ServicesOptimisation & Cost
Optimisation & Cost
Management
A feature that costs $50/month in testing can cost $50,000/month in production.
Engagement
Engineering & Governance
Typical Duration
2 – 4 weeks
Making AI systems faster, cheaper, and better, simultaneously. The engineering that turns an expensive, slow prototype into something economically viable and performant enough for production. Cost, latency, and quality optimised together.
What we optimise
Cost Reduction
Model routing (simple queries to cheaper models, complex to powerful ones, typically 30–50% savings). Prompt compression. Semantic caching. Batch processing for non-real-time workloads.
Latency Reduction
Streaming for perceived speed. Parallel execution of independent steps. Pre-computation for predictable queries. Retrieval optimisation. Infrastructure tuning and geographic routing.
Quality Improvement
Systematic prompt engineering with evaluation suites. Structured outputs to reduce errors. Dynamic few-shot example selection. Evaluation-driven iteration targeting specific failure modes.
How it works
Profile — Step 1
Instrument the system. Token consumption per feature, latency per step, cache hit rates, error rates, quality scores.
01
Profile — Step 1
Instrument the system. Token consumption per feature, latency per step, cache hit rates, error rates, quality scores.
02
Identify — Step 2
Find highest-impact opportunities. The feature that’s 60% of cost. The step that’s 70% of latency.
Identify — Step 2
Find highest-impact opportunities. The feature that’s 60% of cost. The step that’s 70% of latency.
Implement — Step 3
Each optimisation validated against quality benchmarks. No cost reduction that degrades quality.
03
Implement — Step 3
Each optimisation validated against quality benchmarks. No cost reduction that degrades quality.
04
Monitor — Step 4
Ongoing tracking of cost, latency, and quality with alerts when metrics drift.
Monitor — Step 4
Ongoing tracking of cost, latency, and quality with alerts when metrics drift.
Deliverables
What you get
- Cost analysis with breakdown by feature, model, and request type
- Implemented optimisations with measured impact
- Quality evaluation proving no degradation
- Monitoring dashboards for cost, latency, and quality
- Optimisation playbook for ongoing improvement
Cost OptimisationLatencyCachingModel RoutingRedisEvaluationMonitoringLiteLLM
AI costs growing faster than the value it’s delivering?
We’ve optimised AI systems at production scale. The cost-quality-latency triangle has a sweet spot. We help you find it with data, not guesswork.