New: a readout deck for your customer meeting, and the Lens workshop. See it

Agentic AI readiness, assessed in an afternoon.

  • For AWS and Azure consulting partners
  • Scored across seven pillars
  • Delivered under your brand
  • Amazon Web Services
  • Microsoft Azure
  • Read-only collector
  • Hosted in the UK
  • Open-source collector

Score any AWS or Azure estate for agent readiness

Customers Northgate Financial Q3 re-scan

Sample data
Ready to pilot

100% coverage · 38 of 38 checks assessed

  • P1Platform & Model Access
    67
  • P2Identity & Access
    66
  • P3Data Foundations
    94
  • P4Security & Network
    66
  • P5Observability & Operations
    65
  • P6Cost & Capacity
    73
  • P7Governance & Compliance
    79
  • PartialHighModel invocation logging is enabledbedrock.get_model_invocation_logging_configuration · loggingConfig: CloudWatch Logs (/bedrock/invocations)
  • PartialHighGuardrails block prompt attacksbedrock.get_guardrail · PROMPT_ATTACK.inputStrength: LOW
  • PartialHighLong-lived IAM user access keys are minimisediam.get_credential_report · access_key_1_last_rotated: 2024-12-20T14:40:00Z
  • FailHighOver-privileged roles are limitediam.get_account_authorization_details · policy: AdministratorAccess

38 AWS and 36 Azure checks across seven pillars, aligned to the AWS Agentic AI Lens and Microsoft's AI guidance.

Features

  • AI and agent controls first
  • Evidence on every finding
  • Root-cause grouping
  • Coverage and confidence
  • Run-to-run comparison

Know what's already running

Customers Northgate Financial Q3 re-scan

Sample data

Current AI usage

2 models in use: about 61k calls and 80M tokens in the last 30 days, and about US$265 a month on Amazon Bedrock and SageMaker. Totals only, never prompts or outputs. Not scored.

Models, last 30 days

ModelRegionCallsTokens in / out
amazon.nova-pro-v1:0Europe (London)48k61.4M / 9.8M
amazon.titan-embed-text-v2:0Europe (London)13k8.7M / 0

AI spend by month

  • Jun 2026US$218
  • Jul 2026US$270
  • Aug 2026US$307

Average US$265 a month, mostly Amazon Bedrock.

AI outside Amazon Bedrock

Signs of AI used outside Bedrock (13 secrets and 40 Lambda functions checked by name). Worth asking who owns it and whether it follows the same guardrails and logging. Counts only: names are matched on the customer's machine and never leave it. Not scored.

  • OpenAI: 2 secrets and 3 Lambda functions named for it
  • Anthropic: 1 secret named for it

AI usage, spend and AI outside the platform, read as totals by the collector: never prompts or outputs.

Features

  • Models, calls and tokens
  • Monthly AI spend
  • Signs of AI outside Bedrock or Foundry
  • Actual spend beside the pilot's cost

Turn findings into a 90-day plan

Customers BrightBasket Retail Readiness assessment

Sample data
  1. Today20/100Not ready
  2. After Wave 154/100Foundational
  3. After Wave 279/100Ready to pilot
  4. After Wave 3100/100Ready to scale

Wave 1Days 0–30

  • S3 public access is blocked at account levelCritical
  • Root user has MFA enabledCritical
  • Multi-region CloudTrail logging is onCritical
  • Model invocation logging is enabledHigh

Wave 2Days 31–60

  • Long-lived IAM user access keys are minimisedHigh
  • Cost allocation tags are activeMedium
  • A data catalogue is in useMedium
  • Sensitive data discovery is enabledMedium

Wave 3Days 61–90

  • AWS Organizations is in useHigh
  • Centralised workforce identity (IAM Identity Center)High
  • A landing zone is in placeMedium
  • Regions are restricted for data residencyMedium

Every fix shows the score it earns, wave by wave, so your customer sees what the work buys.

Features

  • Three waves, ordered by dependency
  • Blockers first
  • Projected score per wave
  • Ready-to-run fixes: CLI, Terraform, CloudFormation, Bicep

Choose the first agent pilot with your customer

Customers Northgate Financial Q3 re-scan

Sample data
Use-case prioritisation: value against feasibilityPolicy FAQ assistant: value 4, feasibility 5, Low risk. Complaint triage: value 5, feasibility 3, Medium risk. KYC document checks: value 5, feasibility 2, High risk. Meeting summaries: value 2, feasibility 5, Low risk. Payment exception handling: value 4, feasibility 2, High risk. Internal IT helpdesk: value 2, feasibility 2, Medium risk.Fix foundations firstStart hereParkNice to have1122334455Feasibility →Value →123456
  1. 1Policy FAQ assistant · recommended first pilot · value 4, feasibility 5, low risk
  2. 2Complaint triage · value 5, feasibility 3, medium risk
  3. 3KYC document checks · value 5, feasibility 2, high risk
  4. 4Meeting summaries · value 2, feasibility 5, low risk
  5. 5Payment exception handling · value 4, feasibility 2, high risk
  6. 6Internal IT helpdesk · value 2, feasibility 2, medium risk
Low riskMedium riskHigh riskRecommended first pilot

Agent blueprint

Policy FAQ assistant

  • ModelAmazon Bedrock
  • Agent runtimeAmazon Bedrock AgentCore Runtime
  • KnowledgeAmazon Bedrock Knowledge Bases
  • Tool accessAmazon Bedrock AgentCore Gateway
  • GuardrailsAmazon Bedrock Guardrails

Model cost about $46.50–$93.00 a month3,000 runs a month, at list prices

Value, feasibility and risk scored together, with a recommended first pilot and its blueprint.

Features

  • Use-case workshop
  • Recommended first pilot
  • Agent blueprint
  • Running-cost estimate

Run the review workshop, pre-filled from evidence

Customers Northgate Financial Q3 re-scan

Sample data

Agentic AI Lens workshop14 of 40 questions done

18 of 146 best practices evidenced from configuration; 35 more answered in the workshop.

AGENTOPS06How do you implement testing, evaluation, and validation frameworks?
  • FailEvaluate and track ongoing agent performance

Tested by hand before release; no evaluation set yet.

Customer-reported, via workshop
AGENTOPS01How do you establish operational practices for agentic AI systems?

The policy FAQ assistant has a named owner (HR operations). Success criteria not yet written down.

Customer-reported, via workshop

Every best practice in the AWS Agentic AI Lens, evidenced from configuration where it can be, and answered with your customer where it can't.

Features

  • Lens evidence pack (PDF)
  • Answers labelled customer-reported
  • Progress across all 40 questions
  • Microsoft guidance mapped for Azure

Deliver it under your brand

Customers Northgate Financial Q3 re-scan

Sample data
Your logo
Agentic AI readinessNorthgate Financial
Prepared by your firm
  • Executive summary Approved
  • Identity & Access Approved
  • Data Foundations Approved
  • Root causesAI draft, not yet approved
  • RoadmapAI draft, not yet approved

AI drafts the narrative. Your consultant approves every word. Then resell it at your own price.

Features

  • Executive PDF
  • Readout deck (PowerPoint)
  • Technical workbook with fixes
  • Agent blueprint
  • Re-scan reminders every 90 days

From collector to report.

  1. 01

    Your customer runs the collector

    A read-only Python script in AWS CloudShell or Azure Cloud Shell. It produces one file per AWS account, or one for the whole Azure tenant.

  2. 02

    The files come to you

    Your customer sends them, or uploads them through a private link. Any missing permissions are flagged before you evaluate, so no run is wasted.

  3. 03

    Review and run the workshop

    Scores, evidence, root causes and a roadmap; then pick the first pilot with your customer.

  4. 04

    Approve and export

    Approve each AI-drafted section and export the report, readout deck, workbook, blueprint and Lens pack under your brand.

Built for your customer's security team.

curl -fsSLO https://flightglass.io/collector/aws/flightglass_collector.py
python3 flightglass_collector.py \
  --regions eu-west-2,us-east-1 \
  --output flightglass-bundle.json

Read-only by design

AWS: the SecurityAudit and ViewOnlyAccess policies plus eight read actions. Azure: Reader, Security Reader, Cost Management Reader and Entra Global Reader. Nothing can be changed.

Metadata, not data

Configuration and AI usage totals only, from an allow-list of fields: no secret values, no data contents, no prompts or model outputs. Spend on anything but AI services is dropped on your customer's machine.

Raw files deleted after 90 days

Collector files are deleted automatically; results stay until you delete the assessment, which you can do at any time.

Your customer stays in control

They run the collector in their own cloud shell and share the resulting files, by email or a private upload link. Flightglass never holds credentials for their accounts.

A person approves every word

Scores come from rules, never from AI. Claude drafts the narrative from the findings; nothing is exported until a consultant approves each section.

Audited and hosted in the UK

Every upload, export, approval and deletion is in your firm's audit log. Hosted in London; each firm's data is isolated from every other.

Start free. Pay per assessment or subscribe.

Prices exclude VAT · Resell assessments at your own price

Pay as you go

Buy assessments when you need them. Every assessment includes re-scans and a white-label report.

Free

£0

Your first assessment, up to 5 accounts or subscriptions, with 1 re-scan within 30 days. Marked as a free trial.

Assessment

£950each

Up to 25 AWS accounts or Azure subscriptions, with 2 re-scans within 12 months.

Assessment, large estate

£1,950each

Any size (26+ accounts or subscriptions), with 2 re-scans within 12 months.

Bundle of 5

£4,000for 5

Five assessments at £800 each, each with 2 re-scans within 12 months. Use them within 12 months of purchase.

Subscriptions

For firms running assessments every month. No minimum term; annual billing gets about two months free.

Partner

£2,500per month

or £25,000 a year

5 assessments a month (60 a year, pooled, on annual billing), 10 consultants, 4 re-scans each. Extra assessments £450.

Partner Pro

£4,500per month

or £45,000 a year

Unlimited assessments (fair use), unlimited consultants, large estates included, 12 re-scans each, priority support and annual invoicing.

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