FOUNDED 2026Backed by Google for StartupsListed on CNCF Landscape
Built by engineers, for engineers.
We started Infravox in 2026 because we were tired of 3AM incident pages, manual root cause analysis, and cloud bills nobody understood. We knew AI could do better — so we built it.
< 60s
Avg detection time
94%
RCA accuracy
78%
Auto-resolve rate
$8.3K
Avg monthly savings
INFRAVOX AI IS
✓Autonomous Infrastructure Operating System
✓Infrastructure-native intelligence platform
✓AI SRE layer — monitors, reasons, remediates
✓Self-healing cloud infrastructure engine
NOT ANOTHER
✗AI chatbot for DevOps
✗Observability dashboard wrapper
✗GPT prompt playground
✗Monitoring tool with pretty charts
Our Mission
Every engineering team deserves an AI SRE that never sleeps — one that detects problems before they become incidents, understands root cause in seconds, and executes safe fixes automatically. We're building that for every team on earth.
🚫
No more 3AM pages
AI detects and resolves incidents before your on-call engineer is paged.
⚡
RCA in seconds
94% confidence root cause analysis across logs, metrics, and topology.
☁️
One platform, every cloud
AWS, GCP, Azure, K8s — one unified operational context.
🧠
AI explains its reasoning
Every insight shows evidence and confidence. No black boxes.
The Team
Operators and engineers who've been in the trenches — building, scaling, and fixing infrastructure at high-growth companies.
Shivam Singh
CEO & Co-Founder
Technical founder with deep expertise in Kubernetes, cloud-native systems, and AI-driven infrastructure automation. Previously led DevOps and platform engineering at scale.
Connect your infrastructure and have Infravox AI monitoring in under 5 minutes.
1
Sign up & log in
Visit infravox.ai/login and create your account. Sign in with your work email or via Google SSO. New users can start on the Free tier — no credit card required.
2
Connect your first integration
Go to Settings → Integrations and connect your cloud provider (AWS, Azure, GCP) or Kubernetes cluster. Takes under 2 minutes.
3
Add a Git repository
Under Code Review → Connect Repo link GitHub, GitLab, Bitbucket, or Azure Repos to enable AI PR reviews and code scanning.
4
Watch AI agents activate
Within minutes the SRE, DevOps, Security, and FinOps agents begin scanning your stack and will surface the first insights on your dashboard.
5
Enable Auto-Remediation
Go to Settings → Auto-Fix and toggle on auto-remediation for safe actions like pod restarts and rollbacks. All actions are logged with full audit trails.
Tip
You can connect as many integrations as your plan allows. The Growth plan supports unlimited integrations and repos. Start on the Free tier — no credit card needed.
How It Works
Every alert goes through a 6-step autonomous pipeline before you're notified — or before it auto-resolves.
01
Signal Detection
Metrics, logs, and traces are ingested continuously. Anomalies trigger within 60 seconds.
02
AI Triage
The AI Orchestrator dispatches the right specialist agent based on signal type.
03
Root Cause
Agent correlates logs, deployments, and topology to determine root cause with 94% confidence.
04
Fix Proposal
A ranked list of safe, reversible fixes is generated — restart, rollback, scale, or patch.
05
Auto-Execute
With auto-fix enabled, the safest action runs immediately and is verified. Full audit trail.
06
Resolution
Incident closes, postmortem is generated, and learnings update the AI model.
AI Agents
Five specialist agents collaborate through an AI Orchestrator to handle every operational task autonomously.
Your 24/7 site reliability engineer. Monitors all services and resolves incidents in seconds.
< 60s
Avg detection time
94%
RCA confidence
78%
Auto-resolve rate
94s
Avg MTTR
The SRE Agent continuously ingests metrics, logs, and traces from all connected integrations. When an anomaly is detected it immediately:
Correlates the signal with recent deployments, config changes, and topology
Queries the log intelligence engine for error patterns in the last 5 minutes
Scores potential root causes using ML-trained models from historical incidents
Generates a blast-radius analysis to understand downstream impact
Proposes a ranked list of safe, reversible fix actions
Executes the fix (if auto-remediation is enabled) and verifies resolution
Note
The SRE Agent integrates with PagerDuty, Opsgenie, Slack, and Microsoft Teams. When a fix is auto-applied, the on-call alert is automatically resolved and a postmortem is generated.
DevOps Agent
Monitors every deployment, detects pipeline failures, and triggers automatic rollbacks.
Connected to GitHub Actions, GitLab CI, Jenkins, ArgoCD, CircleCI, and Azure Pipelines, the DevOps Agent watches every pipeline run in real time. It correlates new deployments with system health metrics — and rolls back automatically if a regression is detected within the first 5 minutes of a release.
# Example: automatic rollback trigger eventevent: deployment.regression_detected
service: api-gatewaydeploy: v2.4.1 → rollback to v2.4.0reason: error_rate +340% within 90s of deployaction: kubectl rollout undo deployment/api-gateway
status: RESOLVED in 47s
Incident Management
From detection to resolution — fully automated. Average time to resolve: 94 seconds.
ML-powered diagnosis with 94% confidence across infrastructure, code, and dependencies.
Every alert triggers a full RCA pipeline. The AI correlates signals across your entire topology — services, databases, cloud resources, and recent code changes — to identify root cause with high confidence.
Tip
Infravox AI uses a combination of log embedding similarity, deployment diff analysis, and topology graph traversal to attribute incidents. You can see the full reasoning chain in each incident's detail view.
Auto-Remediation
The killer feature. Alert → diagnose → fix → verify — all in under 94 seconds.
1
Alert fires
A metric threshold, log pattern, or anomaly detection triggers the pipeline.
2
AI analyzes
The Orchestrator dispatches the relevant agent. Logs, metrics, and deployment history are correlated.
3
Fix proposed
A ranked list of safe, reversible actions is generated — restart, rollback, scale, or patch.
4
Auto-execute
With auto-fix enabled, the top-ranked safe action executes via MCP tools (kubectl, AWS SDK, etc.).
5
Verify & close
The agent waits for health checks to pass, then closes the incident and notifies the team.
Warning
Auto-remediation only executes pre-approved action types. Destructive actions (delete, scale-to-zero, production config changes) always require human confirmation regardless of settings.
Observability
Full-stack visibility across metrics, logs, traces, and Kubernetes — all in one place.
AI-powered log analysis that turns noise into insight.
Infravox ingests logs from Loki, ELK Stack, ClickHouse, CloudWatch, and GCP Logging. The Log Intelligence engine clusters similar log lines, detects anomalies in frequency or content, and surfaces the relevant context for each incident automatically.
// Example: AI surfaces the relevant log cluster automaticallyERRORapi-gateway db-connection-pool timeout (47 occurrences)
WARNapi-gateway upstream latency p99 = 3.4s
INFOai-sre-agent root cause identified — auto-fix queued
Git & Code Intelligence
AI-powered PR reviews, SAST scanning, and pipeline monitoring across all major Git platforms.
The Git Agent uses a combination of LLM-powered code understanding and traditional SAST pattern matching. Critical security findings automatically block merges when merge protection is enabled.
SAST Code Scanning
Detect security issues before they hit production.
Every PR triggers a full static analysis scan. Results are posted as inline code comments with severity ratings, remediation guidance, and links to relevant CVE records.
Secrets & API keys
SQL / Command injection
CVE dependency scan
IaC misconfigurations
Insecure crypto usage
OWASP Top 10 patterns
Security
Continuous security posture management across your entire infrastructure and code.
Automated compliance checks across six major frameworks.
SOC 2 Type II
87 checks
HIPAA
64 checks
GDPR
42 checks
ISO 27001
114 checks
PCI-DSS
78 checks
CIS Benchmarks
200+ checks
Tip
Compliance reports can be exported as PDF or JSON and are updated continuously as your infrastructure changes. Available on the Unlimited and Enterprise plans.
Cost Optimization
The FinOps Agent identifies waste and saves teams $2K–$15K/month on average.
