Catch AI Spend Problems Before They Become a Bill

Govern access before spend happens

AI spend moves fast, and the first sign of a problem is usually the invoice. A misattributed workload, a retry loop burning tokens, a guardrail scan costing more than the request it's protecting — none of that shows up until someone goes looking, and by then it's already cost real money.

• Spend spikes get noticed after the bill, not before
• Misattributed or misrouted spend hides in aggregate numbers
• Retry and failure waste rarely gets a dedicated line item
• Guardrail scans can quietly cost more than the requests they protect

One policy layer across model usage

Cloptima's intelligence engine continuously analyzes gateway and telemetry data and surfaces what it finds directly in the console's Recommendations tab: spend and usage anomalies against a workload's own baseline, attribution and pricing findings, retry and failure-waste findings, guardrail-overhead findings, and unit-economics anomalies. Each item is ranked by dollar impact with evidence attached, and you can acknowledge or dismiss it right from the feed.

• Spend and usage anomalies measured against each workload's own baseline
• Attribution and pricing findings — spend that's misattributed or mispriced
• Retry and failure-waste findings
• Guardrail-overhead cost findings
• Unit-economics anomalies (cost per answer, ticket, workflow, or customer)
• Ranked by dollar impact, with acknowledge/dismiss actions and audit-ready evidence

Start with one app, then expand

Turn on the governed gateway or telemetry ingest for your highest-spend apps, then check the Recommendations tab after the first few days of traffic to see what the intelligence feed surfaces.

Built for private production AI

Findings are evidence-backed and ranked, not a raw alert firehose — each one carries the context needed to act on it or dismiss it with confidence, and dismissed items stay out of the way going forward.