Services
AI Cost and Performance Optimization
Improve model choice, prompts, agent loops, infrastructure, and usage visibility without compromising reliability.
Typical engagements identify 20–50% cost reductions or latency wins with measurement before and after.
Who this is for
- Teams surprised by production LLM bills
- Products where slow agents hurt conversion
- Leaders preparing to scale AI features
Problems we solve
- Token spend grows faster than usage
- Agents loop or over-call tools
- No dashboards for cost per task
- Model upgrades break quality silently
What we build
Model & prompt optimization
Right-size models, compress prompts, and cache where safe.
Agent-loop efficiency
Reduce redundant tool calls and add stop conditions with evaluation suites.
Infrastructure tuning
Batching, routing, and regional deployment for latency-sensitive paths.
How it works
Audit in week 1, experiments in weeks 2–4, production rollout and monitoring in weeks 5–8.
Get a Free EstimateTechnology we use
- LLM gateways
- Caching
- Eval frameworks
- Metrics & tracing
Frequently asked questions
- Will optimization hurt answer quality?
- We regression-test against your eval set before any production change.
- Can you optimize third-party agents we built?
- Yes, if we can access logs, prompts, and infrastructure configuration.
- How do you report savings?
- Dashboards for cost per conversation, task, or user segment—agreed in discovery.
Related services
Ready to get started?
Tell us what you want to automate or build. We will send a free project estimate and a clear timeline within 48 hours.