Visual Canvas
Design infrastructure with nodes and connectors; instant validation.
Cloud & AI Infrastructure • Cost Intelligence • AI Agents
Platform Capabilities
Capabilities across the infrastructure lifecycle—from pre-deployment cloud and LLM cost intelligence to governed AI agents that build and operate cloud, Kubernetes, and AI agent infrastructure.
Cloud Infrastructure
CrftInfrai Cloud Infrastructure
Visually design cloud infrastructure across AWS, GCP, Azure, and OCI. Generate clean Terraform, download a ready-to-use project, and let AI document and explain everything.
- Drag-and-drop resources on a visual canvas
- Multi-cloud: AWS, GCP, Azure, OCI
- Generate production-ready Terraform files
- Download full Terraform project as ZIP
- Auto-generated README for cloud account setup, remote state, and Terraform execution
- Explain My Infra: plain-English breakdown and optimizations
- Predict cost for the exact generated code using pricing APIs
Visual BuilderTerraform ExportREADME Setup DocsExplain My InfraCost Prediction
Multi-Cloud
AWS • GCP • Azure • OCI.
Terraform Export
Clean, validated Terraform files.
Download as ZIP
Project-ready structure.
README Docs
Auto-generated and clear.
Explain My Infra
Plain-English insights.
AI Cost Intelligence
CrftInfrai AI Cost Intelligence
Move beyond token price and understand the economics of completed AI work. Compare models, forecast workloads, and evaluate AI against human effort before you scale.
- Cost per Task
- Cost per Successful Task
- Human vs AI
- LLM cost comparison across providers
- Workload cost forecasting
Cost per TaskWorkload ForecastingModel Comparison
Cost per Task
Translate token and tool usage into the cost of a completed task.
Cost per Successful Task
Account for retries, failures, and success rates when comparing AI outcomes.
Human vs AI
Compare AI workload economics with the human effort it replaces or augments.
LLM Cost Comparison
Compare input, output, tiers, and context economics across model providers.
Workload Forecasting
Model expected usage and spend before workloads reach production scale.
Cloud Cost Insights
CrftInfrai Cloud Cost Insights
Give us CPU, RAM, and storage, and CrftInfrai fetches matching instance types across AWS, GCP, Azure, and OCI with an at-a-glance cost breakdown.
- Input CPU, RAM, and storage requirements
- See matching VM and instance types by provider
- Real-time prices from cloud pricing APIs
- Visual chart with hourly and monthly breakdown
- Highlights the best value option for your needs
Cross-Cloud Search
AWS • GCP • Azure • OCI.
Spec-to-SKU Match
CPU/RAM requirements mapped to instance types.
Storage Options
Disk tiering and sizing options.
Breakdown Charts
Hourly and monthly cost views.
Best Option
Auto-ranked recommendations.
Real-Time Pricing
Provider pricing APIs.
AI Cost Intelligence
AI Cost Intelligence Catalog
Compare LLM, image, speech, and vector model pricing across providers before you integrate. Forecast usage and pick the right model for your budget.
- Side-by-side pricing: OpenAI, Anthropic, Google, Azure, Bedrock, OCI
- LLMs: input/output per-token costs, tiers, and context length
- Image models: per-image generation costs
- Speech: STT/TTS pricing comparison
- Vector, embeddings, and infrastructure costs
LLM PricingImage ModelsSpeech STT/TTSVector & Embeddings
Estimator
Usage to monthly forecast.
Model Catalog
Filter by provider and tier.
Context Length
Compare token windows.
One Platform
AI cost intelligence and cloud cost intelligence together.
Cloud Infrastructure
CrftInfrai AI Cloud Builder
Generate Terraform from pre-built templates or describe what you need in natural language. The output includes a full setup with README and Explain My Infra.
- Pre-built templates such as EKS + RDS + ArgoCD, GKE + Cloud SQL, and AKS + Monitoring
- Production-grade Terraform output with clean structure
- Auto-generated README for cloud account setup, remote state, and Terraform execution
- Explain My Infra: components, costs, and optimizations
- Prompt panel: describe infrastructure and get Terraform for supported clouds
- AWS • GCP • Azure • OCI supported
Templates Library
Complete stacks, ready to go.
Prompt to Terraform
Any cloud, any supported resource.
README Docs
Auto-generated and clear.
Explain My Infra
Plain-English insights.
Prod-Ready TF
Deterministic and validated.
Multi-Cloud Support
AWS • GCP • Azure • OCI.
Kubernetes Agents
CrftInfrai Kubernetes Agents
CrftInfrai AgenticOps brings named AI agents into Kubernetes, DevOps, SRE, GitOps, and platform operations. The platform detects incidents, analyzes root cause, generates remediation plans, requests approval when risk is high, creates GitOps changes, and verifies recovery.
Incident DetectionKubernetes RCASafe RemediationGitOps ChangeRecovery VerificationApproval & Governance
DetectDiagnosePlanEvaluate RiskApproveGitOpsVerify
K8s Health Agent
Detects unhealthy pods, deployments, namespaces, nodes, and cluster-level degradation signals.
K8s Diagnosis Agent
Performs RCA for ImagePullBackOff, CrashLoopBackOff, Pending pods, rollout failures, and scheduling issues.
K8s Remediation Agent
Generates safe remediation plans with confidence scoring, risk checks, policy awareness, and approval readiness.
Operator Agent
Coordinates controlled operational actions such as restart, rollback, scale, inspect, and workload-level execution.
GitOps Agent
Creates GitOps-ready changes and pull requests instead of directly mutating production workloads.
ArgoCD Sync Agent
Tracks ArgoCD sync, drift, rollout state, application health, and post-change deployment status.
Cluster Upgrade Agent
Plans Kubernetes upgrades with compatibility checks, pre-upgrade validation, risk analysis, and safer rollout paths.
Recovery Verification Agent
Verifies whether remediation restored pod, deployment, namespace, service, and cluster health.
Governance Agent
Adds approval gates, audit trail, risk scoring, production safeguards, and controlled remediation policies.
AgenticOps Workflow
From Kubernetes incident to verified recovery with approval, GitOps, and auditability built in.
1. Detect Incident
Detect unhealthy pods, degraded deployments, failed rollouts, node pressure, scheduling failures, and namespace issues.
2. Analyze Root Cause
Classify whether the issue is image-related, config-related, resource-related, rollout-related, network-related, or scheduling-related.
3. Generate Remediation Plan
Generate an explainable remediation plan with evidence, confidence, risk score, and recommended next action.
4. Request Approval
Request human approval when the action is risky, production-impacting, destructive, or policy-sensitive.
5. Create GitOps Change
Create pull requests for Kubernetes YAML, Helm, Kustomize, ArgoCD, or Terraform changes instead of direct mutation.
6. Verify Recovery
Verify that workload, deployment, namespace, service, and cluster health recovered after remediation.
Ready to bring AI agents into your infrastructure workflow?
Explore CrftInfrai's agentic infrastructure platform or see how governed agents can build and operate your infrastructure.