SAVI

Stop Runaway Agents before they turn into unexpected costs

SAVI's multi-signal detection stack fires within 30 seconds of a velocity spike or tool-thrashing pattern - with plain-language incident explanations and full cost context for every alert. This page covers what happens when an agent specifically loses control. For the full anomaly detection system across all spend types, see Anomaly Detection.

  • SAVI detects inefficient or looping AI behavior within 30 seconds using continuous signal-based monitoring
  • Multi-dimensional scoring across cost, reliability, and risk improves visibility and governance of AI systems
  • Every incident includes plain-language explanation of which signals fired and why
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Autonomous agents silently destroy your AI budget while your team sleeps

Modern AI agents are designed to be autonomous - they retrieve documents, call APIs, summarise results, and loop until done. But without guardrails, a single misconfigured agent can make thousands of identical tool calls through the night. Finance discovers the damage on the monthly invoice. Not at 11:43 PM when it started.

A single runaway loop can generate $50,000+ in charges overnight

Standard budget alerts fire daily or weekly - long after the damage compounds.

Zero existing tools detect recursive patterns at runtime and signal a pause

Engineers have to manually triage logs, identify the looping agent, and redeploy - costing hours on top of wasted spend.

Regulated industries face compliance exposure when agents process PII in loops

Without per-call logging you can't prove what happened, when it started, or how much it cost - making post-mortems guesswork.

1
Every call is observed
All LLM requests pass through SAVI's monitoring layer. Policy checks resolve in under 2ms - invisible to your agents.
2
Unusual activity is scored against your baseline
SAVI measures each agent's call rate against its own historical pattern. A sudden spike is caught in seconds, not hours.
3
Runaway token usage and tool cycling are detected
When an agent generates far more output than it consumes or bounces between tools without progress, SAVI escalates its risk score.
4
Signals are combined into a single risk verdict
Cost, reliability, and behavioural signals are weighted together. SAVI fires only when multiple signals agree - no single metric triggers a false alarm.
5
Your team is notified before costs spiral
When the verdict crosses a threshold, your Slack or PagerDuty channel is alerted and the dashboard updates - within one second.

Detection Pipeline · Real-time · < 2ms overhead

Five signals, one composite score, in real time

Every AI request is evaluated in real time using multiple detection signals, all within the ingest path and with negligible overhead. These signals are combined into a structured view of cost, reliability, and risk. Different workloads behave differently. SAVI understands the difference between agent loops and normal high-throughput pipelines and adjusts detection accordingly.

  • Quick integration via a lightweight SDK wrapper for all major AI providers - no complex setup required
  • Govern AI behavior with tailored controls for each workload type across the enterprise
  • Track AI behavior through a clear progression from expected activity to detection, escalation, and investigation

Flag, alert, and investigate - without breaking agent determinism

When a threshold is breached, SAVI immediately flags the incident, fires a structured alert, and streams the detection.

  • Enterprise-ready integrations across communication and incident response channels
  • Continuous, real-time visibility into AI incidents as they are detected across the system
  • Complete alert context includes detection signals, scoring, incurred cost, and projected short-term financial exposure
Agent
summarise-pipeline-v2
Loop Pattern
247 calls/min
critical
Cost Prevented
$38,200 est.
ok
Pause Signalled
11:43:18 PM

SAVI Slack alert - #finops-alerts · SAVI FinOps Bot

timestampagenttokenscost impactdecisionmodel
11:43 PMsummarise-pipeline-v22.4M$38,200Pause signalledgpt-4o
09:18 AMcustomer-support-bot180K$420Alertedclaude-3-5
Yesterdaydoc-retrieval-agent890K$12,100Pause signalledgemini-1.5
2 days agoinvoice-processor44K$110Loggedgpt-3.5
3 days agocode-review-bot640K$7,800Pause signalledgpt-4o

Swipe to see all columns →

Audit Log · Agent Loop Events · Showing 5 of 23 events this month

Audit-ready evidence for every AI action

SAVI writes an immutable audit log for every detection event - agent ID, token counts, cost impact, the pause signal raised, and the model version used to classify it. Every field is cryptographically signed at write time. When a regulator, auditor, or board asks what your AI did and what it cost - the record is already there.

  • Tamper-proof log storage - every detection event cryptographically signed and immutable from the moment it is written
  • 18–24 months of full-granularity retention - no summarisation, no sampling, no gaps
  • Export to CSV or JSON, or push directly to your SIEM - fits any compliance or incident response workflow
  • Role-based access views - executives see cost and risk summary, engineers see the full call trace

Plain-language explanations on every incident

Every alert SAVI fires comes with a plain-English explanation of exactly what triggered it - written for operators, not engineers. You don't need to decode signal scores or read log files. SAVI tells you which pattern fired, how far above normal it was, and what it means for your AI budget. For regulated entities, documented explainable decisions are a governance control, not a nice-to-have.

  • Every alert names the pattern that fired, how far above normal it was, and the estimated cost impact
  • Plain-English incident summaries - written for operators and compliance reviewers, not ML engineers
  • Mark any alert as a true or false positive to improve future detection accuracy
Agent
summarise-pipeline-v2
Pattern detected
Call velocity spike
critical
How far above normal
3.8x the 7-day baseline
Plain-English summary
This agent made 47 calls in 5 minutes - nearly 4x its usual rate. Cost exposure: $38K/hr if unchecked.

Alert Detail · Plain-language explanation on every incident

Projections from early design-partner scenarios

 
Potential cost prevented per runaway loop incident, modelled at under 30 seconds detection time
 
Target median time from loop formation to detection, alert, and Slack notification
 
Loop incidents designed to surface
Goal: zero undetected budget-damage events across design partners
 
Independent detectors on every event
Velocity, token explosion, tool thrashing, spend rate, loop depth

Loop Detection

Do you know if your agents are destroying your AI budget right now?

7 questions. Answer honestly.

Can you see every LLM call across all your AI agents in real time - not on a daily report?

Do you know which agents are calling the same tool with identical inputs more than 5 times per minute?

If an agent started a loop at 11 PM tonight - would you know before 9 AM tomorrow?

Can you detect a runaway agent loop within 30 seconds - without engineering on-call intervention?

Do you have a documented audit trail of every AI agent action your compliance team can access today?

Can you show your CRO or CISO exactly which AI agents processed PII - and whether they looped on it?

Could your organisation survive a $100K runaway agent loop discovered 3 days after it started?

This checks one slice of your AI estate. Take the full AI Cost Ownership Assessment →

Stop finding out about $50K loops on your monthly invoice.

SAVI detects, alerts, and documents every runaway agent in under 30 seconds - with plain-language incident reports your compliance team can use.

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