Trusted by 500+ developers worldwide
The complete platform for operational AI agents
Elvanto turns DevOps and FinOps complexity into executive clarity. Agents handle the operations, leaders get actionable intelligence.
Security Scanner
Scans for vulnerabilities and manages compliance
CI/CD Pipeline
Automates build, test, and deployment workflows
Monitoring Agent
Collects metrics and sends alerts to your team
"Seeing how Elvanto has built upon open source and solid agentic workflow, it gives you the sentries you need to make sure your infrastructure is monitored. Leveraging AI this way is the future, and Elvanto has the right foundation to make this paradigm work."
"Elvanto clearly designed this to work for teams. Every detail—from the agent bundles to the structured insights—was built for their mission of making operations intelligence accessible across the organization."
How Elvanto works: OSS runtime to intelligent insights
Deploy open-source AI agents on your infrastructure. Get structured insights on the Elvanto platform. Make better decisions with intelligent automation.
Edit Agent: aws-cost-explorer
Analyzes AWS Cost Explorer data to identify spending trends, cost anomalies, and optimization opportunities across services
Agent Configuration
Edit the agent's prompt file. After saving, run stn sync environment to apply.
1---2metadata:3 name: "aws-cost-explorer"4 description: "Analyzes AWS Cost Explorer data to identify spending trends,5 cost anomalies, and optimization opportunities across services"6 tags: ["station", "agent"]7 # Data ingestion classification for Elvanto8 app: "finops"9 app_type: "investigations"10model: gpt-4o-mini11max_steps: 1512tools:13 - "__get_cost_and_usage"14 - "__get_cost_forecast"15 - "__get_anomalies"16 - "__get_rightsizing_recommendations"1718input:19 schema:20 type: object21 properties:22 userInput:23 type: string24 description: User input for the agent25 required:26 - userInput2728output:29 schema:30 properties:31 total_cost:
Output Schema
Schema Properties
Output Schema Using YAML controls
properties:
total_cost:
type: number
breakdown_by_service:
type: array
top_cost_drivers:
type: array
anomalies_detected:
type: array
recommendations:
type: arrayInvestigates AWS cost spikes by analyzing Cost Explorer data...
Engineering installs OSS Station once
1. Install Station
Open the Elvanto Station setup guide above.2. Start Station
stn up --provider openai --api-key sk-your-key✅ Web UI at http://localhost:8585 for managing tools, bundles, and builds
✓ Bundles installed successfully
Engineering installs agent bundles
aws-cost-explorer
Edit agent configuration
1metadata:2 name: "aws-cost-explorer"3 app: "finops"4model: gpt-4o-mini5max_steps: 156tools:7 - "__get_cost_and_usage"8 - "__get_anomalies"9output:10 schema:11 properties:12 total_cost:13 type: number
Output Schema
Engineering customizes bundles for your workflow
Deployment
Deploy agents to your infrastructure
Engineering deploys agents on your infrastructure
Run Details #18
Structured Output (JSON)
{
"total_cost": 235943.58,
"currency": "USD",
"period": "2026-08",
"breakdown_by_service": [
{
"service": "Amazon EC2",
"cost": 98234.12,
"percentage": 41.6,
"trend": "up"
},
{
"service": "Amazon RDS",
"cost": 67821.45,
"percentage": 28.7
}
],
"anomalies_detected": [
{
"service": "EC2",
"severity": "high",
"cost_impact": 1250.00
}
]
}Engineering monitors agent runs
Agent Data
| Agent | Output |
|---|---|
| cost-analyzer | $235K total |
| anomaly-detector | 3 issues found |
| optimizer | $89K savings |
| cost-breakdown | EC2: 42% |
Leadership views structured data
Build Widget
Transform data into insights
Source Data
| Service | Cost |
|---|---|
| EC2 | $98K |
| RDS | $68K |
| S3 | $35K |
Top Cost Services
EC2 spending increased 12.3% to $98K. Upgrade to xl instances to meet demand spikes.
Leadership views Elvanto's customizable insight widgets
Cost Savings Dashboard
Data-backed insights
Cloud Spending
| Month | Cost |
|---|---|
| Aug 2026 | $1.2M |
| Jul 2026 | $1.36M |
Active Anomalies
| Service | Impact |
|---|---|
| EC2 Spike | $1.2K |
| RDS util | $890 |
Savings Opportunities
| Action | Savings |
|---|---|
| Reserved | $42K |
| Right-size | $28K |
Leadership uses decision views
Data Lineage
Click citations to expand data
Storage egress costs decreased while EC2 saw a 39% spike.
"Storage egress spikes are most frequent RCA"
storage-egress-spike-rca [15 rows]
Leadership views the data lineage of insights
Teams are already optimized.
The tools aren't.
Stop paying engineers to manually gather data. Elvanto surfaces critical insights so leadership can make informed decisions—not just alerts, but actionable intelligence.
Traditional DevOps
Reactive firefighting
Alerts tell you what's broken, not how to fix it
Manual intervention
Engineers pulled from building to fix infrastructure
Knowledge silos
Runbooks gather dust while incidents escalate
Average MTTR: 4+ hours
Agentic DevOps
Autonomous resolution
AI agents execute fixes before you even wake up
Zero context switching
Engineers stay focused on building features
Continuous learning
Every fix improves the system automatically
Average MTTR: <5 minutes
"We don't want more dashboards telling us what's broken. We want systems that fix things while we sleep."— CISO, Startup Acquired for $10B+
No rip and replace required
Elvanto integrates seamlessly with your existing tools. Deploy agents that work with your current infrastructure, not against it.
Powered by Model Context Protocol (MCP) — the open standard for AI tool integration
Built on open standards
Every integration is powered by Model Context Protocol (MCP) servers, ensuring secure, standardized communication between AI agents and your tools.
npx @aws/mcp-server
npx @modelcontextprotocol/server-filesystem
npx @modelcontextprotocol/server-githubReady to augment your stack with AI?
Start with one agent, scale to hundreds. No migration required.
The industry is at an inflection point
Three unstoppable trends are forcing a shift to autonomous operations.
AI crossed the capability threshold
For the first time, LLMs can reliably debug production issues, write fixes, and execute remediation. This wasn't possible 18 months ago.
Accuracy on production fixes
Complexity exceeded human capacity
Kubernetes, microservices, and multi-cloud created an explosion of moving parts. No human can track it all anymore.
More alerts than 5 years ago
Early adopters proved the ROI
Companies using AI agents are already deploying 10x more frequently with 80% less downtime. The results speak for themselves.
Average annual savings
Market adoption is accelerating
As adoption accelerates, companies without AI agents risk falling behind
Don't wait for your competitors to get there first.
All your tools, one platform
Elvanto works with AWS, Azure, Kubernetes, and the tools you already use. No migrations needed.
Works with your stack
AWS, Azure, GCP, Kubernetes - we integrate with them all
AI handles the routine
Let agents manage deployments while your team builds features
Secure by default
Enterprise-grade security with role-based access control
