Primary outcome
Lower cost per request
Start from the buying trigger that matters most, then trace the pipeline changes behind it.
Back to product overview
Optimization Selector
Use your model metadata, architecture, task, constraints, and hardware targets to recommend an optimization strategy across your AI operation — with guardrails on effect estimates, quality gates, and memory ceilings. The ROI Dashboard is included.
Optimization surface
Full AI pipeline
Recommendations span model, data, frameworks, and infrastructure — not one isolated tuning layer.
Included
ROI Dashboard included
See return on investment for the optimizations the Selector proposes, without a separate product buy.
Optimization lenses
One selector, three buying pressures
Start from the pressure your team feels first — speed, energy, or quality — without treating accuracy as optional.
Speed
Prioritize latency where slow responses break the workflow.
Tune model size, serving engine, cache strategy, and context handling to reduce time-to-first-token and end-to-end response time.
- Serving and batching choices matched to the workload
- Prompt and context changes that shorten expensive paths
- Guardrails so faster responses do not quietly erode answer quality
What you get
Recommendations across the full AI operation
The Selector packages model, runtime, and workflow choices into one clear offer so buyers can act on cost, latency, and energy without losing quality as an explicit constraint.
Runtime and latency tuning
Prioritize serving configuration, caching, context handling, and execution choices when response speed is the first pain point.
Efficiency-oriented model changes
Make compression and architecture changes easier to reason about for teams balancing cost and sustainability targets.
Workflow optimization
Show that prompts, routing, and context design can change the economics of the workload just as much as the model itself.
Where it fits
Best for teams who already know optimization is the bottleneck
- Teams already running production AI workloads and feeling infrastructure pressure
- Pilots where speed and spend need to improve before broader rollout
- Stakeholders who want technical changes explained in outcome language instead of tuning jargon
Related offers
Other GAISSA products
Optimization Selector is the lead offer today, but each product stands alone. Explore GAISSA Label when an energy label and A–E efficiency score are the buying trigger, or API Monitoring when provider spend visibility comes first.