Now in beta — FinOpsMind Pro

Cloud costs,
understood.
Then autonomous.

Start with 56 rules and instant Terraform. Graduate to an agentic AI that reasons, learns from your decisions, and acts — with your approval.

Join Pro Beta Learn more
56
Optimisation rules
3
Cloud providers
AI
Agentic engine
FinOpsMind
Available now

Rules-based cost intelligence with instant Terraform remediation. Connect your AWS, Azure or GCP account and get actionable recommendations in minutes.

56 rules Terraform generation Multi-cloud Cost anomaly detection Budget alerts
upgrades to
FinOpsMind Pro
Beta — join waitlist

An agentic AI that reasons across your entire cloud estate, retrieves similar past cases, and autonomously executes or escalates — with a full audit trail.

Claude-powered RAG self-learning Approval gate Slack integration Chain-of-thought audit
Two products. One platform.

Rules today.
Autonomous tomorrow.

FinOpsMind Standard gives your team instant cost intelligence. FinOpsMind Pro gives it an AI agent that gets smarter every time you approve or reject a recommendation.

FinOpsMind Standard
Rules-based
intelligence.

Connect your cloud accounts. Get 56 automated recommendations with generated Terraform, severity scoring, and multi-cloud support — all within minutes.

  • ✓48 AWS + 4 Azure + 4 GCP optimisation rules
  • ✓Auto-generated Terraform HCL for every finding
  • ✓Cost anomaly detection with root cause analysis
  • ✓ETS time-series spend forecasting
  • ✓Budget alerts and policy compliance
  • ✓CI/CD pipeline push for approved remediations
  • ✓Executive summary and carbon emissions reports
  • ✓WebSocket real-time notifications
FinOpsMind Pro
Agentic AI.
Self-learning.

Everything in Standard, plus a Claude-powered orchestrator that reasons across your cloud estate, retrieves similar past cases from memory, and autonomously executes or escalates with full audit trail.

  • ✓Everything in Standard
  • ✓Claude Sonnet agentic orchestrator with chain-of-thought
  • ✓9 registered AI tools callable by the agent
  • ✓RAG memory — learns from every decision you make
  • ✓Tier 1/2/3 approval gate with configurable thresholds
  • ✓Slack Block Kit approval notifications with one-click approve/reject
  • ✓Full reasoning trace stored for every analysis
  • ✓50 pre-seeded case library, grows with your usage
Join the Pro beta →
Rules engine

56 rules. Three clouds.
Every tier of risk.

From one-click safe fixes to architectural migration recommendations — every rule generates Terraform and carries a severity, savings estimate and confidence score.

🗑️
Resource Waste
18
Idle, unattached, and orphaned resources bleeding money silently.
idle_ec2 · unattached_ebs
old_snapshots · idle_eip
unused_ecr · idle_elb
⚙️
Right-sizing
15
OS migrations, Graviton, Fargate, Aurora Serverless — architecture-level savings.
graviton_migration · windows_to_linux
aurora_serverless_candidate
ecs_ec2_to_fargate · spot_candidate
🏗️
Architecture
13
CloudFront, VPC endpoints, cross-AZ transfer, EKS rightsizing and more.
cloudfront_missing_s3
vpc_endpoint_s3_dynamo
eks_node_rightsizing
💳
Commitments
10
Reserved Instances, Savings Plans, RI expiry, convertible RI analysis.
reserved_instance_coverage
savings_plan_gap · ri_expiry_alert
ri_commitment_optimiser
56
rules across AWS · Azure · GCP
Every rule generates Terraform HCL. In Pro mode, rules become AI tools — the agent decides which to invoke based on your query.
Tier 1: Auto-execute Tier 2: Auto + undo window Tier 3: Approval required
⚡ FinOpsMind Pro

An agent that
reasons. Learns.
Acts.

Not another dashboard. A Claude-powered orchestrator that asks your data questions, retrieves similar past cases from memory, and produces a chain-of-thought reasoning trace before recommending anything.

1
You ask in plain English
"What are my biggest savings opportunities this month?"
POST /analyse
2
Context assembled from your data
Spend, anomalies, inventory, budgets — compressed to <2k tokens
Rust · PostgreSQL
3
Past cases retrieved from memory
Similar historical decisions surface via vector search (Qdrant)
RAG · voyage-3
4
Agent reasons and calls tools
Claude Sonnet loops through 9 registered tools — cost, inventory, Terraform
Claude · tool_use
5
Risk scored. Gate applied.
Auto-execute below threshold. Slack approval above it.
Approval gate
6
Decision stored to memory
Your approval or rejection teaches the system for next time
Qdrant · self-learning

What the agent can do

🔍
Cost Anomaly Detective
Correlates spend spikes with deployment events, config changes, and traffic patterns to find the actual root cause.
⚡
Infrastructure Optimiser
Invokes the 56-rule engine as tools, generates Terraform, scores risk, and auto-executes or escalates each finding.
📊
Forecast & Budget Guardian
Rolling 30/60/90-day projections per team, with autonomous Slack alerts when velocity exceeds budget runway.
🏷️
Tag Compliance Sheriff
Scans every resource, infers missing tags from context, auto-fixes what it's confident about, raises tickets for ambiguous cases.
🌍
Carbon Agent
Translates spend into CO₂e, recommends lower-carbon region migrations, generates ESG-ready reports.
💬
FinOps Advisor
The natural language front door. Ask anything — it decomposes your question into parallel tool calls and streams back a synthesised answer.
Approval gate

The agent asks permission
for the things that matter.

Tier 1 actions execute automatically. Tier 2 executes with a rollback window. Tier 3 — or anything above your risk or savings threshold — goes to Slack for your approval. Everything is logged.

Tier 1
Auto-execute
Executed immediately, no human required. Low risk, easily reversible. You are notified after.
vpc_endpoint_s3_dynamo
cloudwatch_log_retention
gp2_to_gp3 · lambda_memory
rds_storage_autoscaling
Tier 2
Auto + undo window
Applied automatically, but you receive a Slack notification with a rollback option for a configurable window.
graviton_migration
scheduled_shutdown
spot_instance_candidate
fargate_rightsizing
Tier 3
Approval required
Requires explicit approval before execution. High architectural impact, commercial decisions, or above your savings threshold.
sql_server_to_postgres
windows_to_linux
reserved_instance_coverage
aurora_serverless_candidate
[ RAG Memory — Qdrant ]
EC2 M5.xlarge → M7g.xlarge (Graviton), prod-api cluster
approved · £840/mo
RDS SQL Server → Aurora PostgreSQL migration
rejected · too risky
27 EBS gp2 volumes → gp3 upgrade across eu-west-1
auto-exec · £240/mo
Savings Plan gap — 3yr all-upfront for EC2 family
approved · £3,200/mo
Shut down dev RDS instances overnight (scheduled)
rejected · dev team objects
VPC Gateway Endpoints for S3 + DynamoDB
auto-exec · £0 cost
50+
cases pre-loaded
∞
grows with usage
1,024
vector dimensions
Self-learning RAG

Gets smarter with every decision you make.

Every analysis result is embedded and stored in Qdrant. When a similar situation arises, the agent retrieves past cases — including your rejections — before making a recommendation.

Reject a suggestion once and the system learns your risk appetite. Approve it and it applies the same logic more confidently next time. No retraining. No manual configuration.

◆ Vector similarity search — voyage-3 embeddings via Anthropic
◆ Qdrant collection pre-seeded with 50 realistic FinOps cases
◆ Every approve/reject decision stored with reason
◆ Reasoning trace auditable — observation → hypothesis → recommendation
Live demo

Ask the FinOpsMind agent.

Powered by Claude. Working against a realistic mock AWS account. Ask anything about costs, waste, or savings.

app.finopsmind.cloud — AI Agent ⚡ Pro
[ Suggested prompts ]
[ Agent response ]
Analysing cost trend
observation
EC2 spend increased £4,200 in 14 days
Three new m5.4xlarge instances launched in eu-west-1 on 28 March with no corresponding deployment tag. No traffic increase detected in ALB metrics for the same period.
hypothesis → evidence → recommendation
Likely abandoned load test environment — not production traffic
CloudTrail shows instances launched by user jenkins-automation at 02:14 UTC. No termination event. Similar case in memory: load test environment left running — approved for shutdown, saved £1,800/month.
Estimated saving: £3,800/month · Risk score: 62 · Tier 2 — auto-execute with undo window
# Generated by FinOpsMind Agent — Terraform remediation resource "aws_instance" "load_test_cleanup" { instance_state = "stopped" instance_ids = ["i-0a1b2c3d", "i-0e5f6g7h", "i-0i9j0k1l"] }
Tier 1 — Auto-executable right now (no approval needed)
14 EBS gp2 volumes → gp3 upgrade
All 14 volumes in us-east-1 and eu-west-1. gp3 is 20% cheaper with better baseline performance. Zero downtime. Reversible in seconds.
£180/month · Confidence: 0.99 · Auto-executing now →
Tier 1 — Auto-executable
VPC Gateway Endpoints for S3 + DynamoDB
High S3 traffic routing via NAT Gateway detected in 2 VPCs. Gateway endpoints are free and eliminate that NAT processing cost entirely.
£340/month · Confidence: 0.97 · Auto-executing now →
Tier 1 — Auto-executable
7 Lambda functions: x86 → arm64 (Graviton2)
Functions on x86_64 with no OS-specific dependencies. arm64 is 20% cheaper at same performance tier.
£95/month · Confidence: 0.94 · Auto-executing now →
Biggest waste area #1 — EC2
6 instances with <5% CPU for 21+ days
Largest offender: r5.2xlarge in eu-west-1, running since January, zero incoming connections for 21 days. Likely a forgotten staging environment.
£1,240/month combined · Tier 2
Biggest waste area #2 — RDS
Multi-AZ enabled on 3 non-production databases
Three RDS instances tagged "staging" with Multi-AZ enabled — doubles the instance cost with no HA requirement in staging.
£680/month combined · Tier 1
Biggest waste area #3 — Commitments
Savings Plan coverage only 34% of compute spend
£12,400/month running on-demand where 1yr no-upfront Savings Plans would cover it. Breakeven at 9 months.
£3,100/month · Tier 3 — requires your approval
Pending approval · Risk score: 78 · Est. saving: £3,100/month
Savings Plan purchase — 1yr no-upfront, compute family
Agent reasoning: EC2 family has run at consistent utilisation for 90 days. No planned workload changes in roadmap tags. Breakeven is 9 months on 1yr plan. Similar case approved by your team in October.
Slack notification sent · Approve / Reject buttons in #finops-alerts
Pending approval · Risk score: 72 · Est. saving: £840/month
Graviton migration — prod-api cluster (M5 → M7g)
Agent retrieved 3 similar cases from memory: all approved, average 19% cost reduction, no performance regression. Recommends blue-green deployment to validate before full cutover.
Terraform plan ready · Awaiting approval
Thinking
← Select a prompt or type your question to try the agent
⚡ FinOpsMind Pro Beta

Be the first to run
an autonomous FinOps agent.

Early access to the Pro agentic engine. Help shape the product. Priority onboarding and direct line to the team.

No credit card. No commitment. We review each application personally.

Pricing

Start free. Scale to autonomous.

No per-seat complexity. Priced on cloud spend under management.

Standard
FinOpsMind
Free during beta

Full rules engine, Terraform generation, multi-cloud support. Up to £50k/month cloud spend.

  • ✓56 optimisation rules
  • ✓Auto-generated Terraform HCL
  • ✓Cost anomaly detection
  • ✓Spend forecasting
  • ✓Budget alerts and policies
  • ✓AWS + Azure + GCP
Most popular
Pro
FinOpsMind Pro
Beta — apply for access

Full agentic AI engine. Claude-powered reasoning. RAG self-learning. Approval gate. Slack integration.

  • ✓Everything in Standard
  • ✓Claude Sonnet orchestrator
  • ✓RAG vector memory (Qdrant)
  • ✓Tier 1/2/3 approval gate
  • ✓Slack approval notifications
  • ✓Full reasoning audit trail
  • ✓9 registered AI tools
Join the beta →
Enterprise
Custom
Talk to us

For enterprise cloud estates above £500k/month. Private deployment, custom rules, SLA, dedicated support.

  • ✓Everything in Pro
  • ✓Private VPC deployment
  • ✓Custom rule development
  • ✓Dedicated onboarding
  • ✓99.9% SLA
  • ✓SOC 2 / GDPR compliance
Get in touch