Right-sizing trims the surface. We cut the work that built the bill.
Most cloud spend isn’t idle capacity — it’s inefficient code and queries forcing you to over-provision. GIIP inherits 30 years of senior engineering experience into AI, tuning source code, query plans and database engines so the workload itself shrinks. Experts protect performance; the bill falls because the work got smaller.
Continuous optimization · no performance trade-off · full transparency.
Cloud spend grows quietly until someone finally looks at the invoice.
Most teams overpay not because of scale, but because optimization is nobody’s full-time job — so waste accumulates month after month.
Waste right-sizing can’t reach
Inefficient queries, N+1 calls, full scans and wrong indexes force you to over-provision. No amount of instance tuning fixes work that shouldn’t exist in the first place.
Idle & orphaned resources
Forgotten instances, unattached volumes and stale environments keep billing long after anyone uses them.
Over-provisioning “to be safe”
Oversized instances and headroom bought out of caution become permanent line items.
No cost ownership
When cost is everyone’s job, it’s no one’s job — so nothing gets right-sized.
Fear of breaking prod
Teams avoid optimizing because a wrong change could cause an outage, so waste stays untouched.
Cut the work, not just the resources.
GIIP treats cost as a first-class operational metric — and traces it to its root. AI agents carrying decades of senior tuning experience optimize code, queries and engines, while senior engineers ensure every change is safe for production.
30 years of tuning, inherited by AI
Optimization judgment built over decades of senior engineering is encoded into AI agents that apply it continuously — and those same engineers review high-impact changes themselves.
Source-level bottleneck removal
AI agents trace hot paths through your code, finding the N+1 calls and redundant work that quietly inflate every instance you run.
Query plan & index optimization
Execution plans, full scans and missing or wrong indexes are surfaced and fixed — the workload shrinks before the hardware has to grow.
DB engine parameter tuning
Memory, connection and cache parameters are tuned to your real workload, reclaiming the headroom that over-provisioning was paying for.
Continuous right-sizing & safe scaling
Once the work is smaller, AI agents match resources to real demand and flex with load — so the savings actually reach your invoice.
Waste detection & cleanup
Orphaned resources and stale environments are found and removed automatically, with a full audit trail.
Cost under control, performance intact
24/7
Continuous optimization, not quarterly
0
Performance trade-off on production
100%
Auditable, reversible changes
↓
Idle and over-provisioned spend
Frequently asked questions
How is this different from other FinOps tools?
FinOps tools look at resources — they tell you an instance is oversized. GIIP looks at why it had to be that size: the source code, the query plans and the engine configuration underneath. Tools optimize what you provision; GIIP reduces what you need to provision in the first place.
Will cost optimization hurt our performance?
No. GIIP treats reliability as a hard constraint. AI agents optimize continuously within safe bounds, and senior engineers review high-impact changes, so savings never come at the cost of production performance.
Which clouds do you support?
GIIP operates across major public clouds and Kubernetes, integrating with your existing accounts and billing rather than requiring migration.
Is this a one-time audit or ongoing?
It is continuous. Waste accumulates constantly, so GIIP optimizes as an ongoing operational function rather than a one-off review.
Stop paying for cloud you don’t use.
Send us your setup. We’ll show you where the spend is leaking — in the code and queries, not just the instance list — and how continuous AI optimization closes the gap.