# Characterizedisk

*/Startups/Characterizedisk*

## Startup Overview

Cloud infrastructure teams manage massive volumes of unstructured digital assets scattered across distributed storage environments. This system automatically profiles and segments distributed cloud storage objects to establish immediate visibility into data lakes and blob storage. It indexes object metadata, classifies contents, and maps storage patterns without requiring data to leave the host network.

Traditional data security posture management tools like Varonis, native scanners like AWS Macie, and brittle custom Python scripts force security teams to choose between exorbitant licensing fees and massive operational overhead. Enterprise data engineering and security operations groups require a method to classify sprawling environments without exposing sensitive payloads to third-party processors.

The engine executes entirely within the customer VPC, guaranteeing that storage objects and derived intelligence never cross trust boundaries. Delivered strictly through a consumption-priced model, it aligns expenses directly with actual scanning volume to provide a deterministic alternative to fixed-tier security billing.

## Startup Founding Hypothesis

**Approach**: that profiles and segments distributed cloud storage objects
**Competitors**:
- [AWS Macie](/Competitors/AWS_Macie)
- [Varonis](/Competitors/Varonis)
- [custom Python scripts](/Competitors/custom_Python_scripts)
**Differentiator2x2**: consumption-priced and executing entirely within the customer VPC

## Startup Solution Coordinate

**Solution**: [VPC Storage Profiler](/Software/VPC_Storage_Profiler)

## Startup Position2x2

```mermaid
quadrantChart
    title Market Positioning
    x-axis External SaaS / Managed --> Entirely In-VPC Execution
    y-axis Enterprise Licensing / Fixed Cost --> Consumption Priced
    quadrant-1 In-VPC Consumption
    quadrant-2 External Consumption
    quadrant-3 Legacy Enterprise
    quadrant-4 DIY / Custom Build
    Characterizedisk: [0.85, 0.85]
    AWS Macie: [0.55, 0.75]
    Varonis: [0.20, 0.25]
    Custom Python Scripts: [0.90, 0.15]
```

## Startup Offer

**Proof**:
- Aimed at healthcare software providers needing to classify 100TB+ of unstructured bucket data without triggering HIPAA compliance risks from vendor access.
- Designed to deliver data classification profiles at less than half the per-GB compute cost of native managed tools like AWS Macie.
- Targeting security teams seeking to map PII distribution across thousands of distinct cloud accounts via local execution.
**Tiers**:
- Name: On-Demand Scan · Price: ~$0.08–$0.15 per GB processed · Inclusions: Ad-hoc profiling of specific cloud storage buckets, evaluating object metadata and sampling payloads via a serverless container deployed directly into the host VPC.
- Name: Continuous Profiling · Price: ~$0.02–$0.05 per GB processed · Inclusions: Automated, event-driven scanning of newly written cloud objects, including continuous segmentation tagging and compliance rule evaluation, requiring a 10TB monthly minimum volume.
**Guarantee**: Zero-egress architecture guarantee: if the deployment requires your payload data to leave your VPC to generate its profiles, your usage fees for that billing period will be waived entirely.
**Business Function**: ProvideService
**Objection Handlers**:
- Will this spike our AWS bill with heavy compute costs? -> The engine is designed to execute using ephemeral Spot instances or serverless functions, keeping local compute overhead strictly proportional to the volume you choose to scan.
- Does this require granting you broad IAM permissions? -> No. It is designed to deploy via a Terraform module that provisions scoped, read-only access limited strictly to the target buckets within your own environment.
- Why not just use AWS Macie? -> Macie forces a premium per-GB cost for managed execution; Characterizedisk provides customizable segmentation heuristics while executing entirely on your own discounted infrastructure.
**Pricing Architecture**: UsageMeter
**Agent Checkout Support**:
- agentic-commerce-protocol

## Startup Brand

**Voice**: Technical and precise, delivering infrastructure facts without marketing exaggeration.
**Tagline**: Profile and segment distributed cloud storage inside your own VPC.
**Icon Concept**: bucket
**Palette Intent**: electric-signal
**Visual Identity**: A high-contrast dark mode aesthetic combines terminal black with neon cyan to reflect the command-line environments where infrastructure teams operate.
**Archetype Reference**: the-sage

## Startup Buyer Chain

**Chain**: Characterizedisk -> Cloud Infrastructure Engineer -> Security and Compliance Team
**Gtm Motion**: Acquires users via a self-serve, single-VPC deployment that profiles an initial tier of cloud storage at no cost. Expands revenue organically through consumption billing as the customer deploys the container across additional VPCs and scales up the volume of objects analyzed.
**Agent Channel**: Designed to publish its discovery and segmentation endpoints to the AWS Bedrock tool registry and OpenAI GPT action schemas, enabling autonomous cloud security agents to trigger object profiling tasks directly.
**Primary Channel**: AWS Marketplace listings and technical SEO targeting cloud security engineers searching for VPC-native alternatives to AWS Macie or open-source S3 scanning scripts.

## Startup Customer Journey

```mermaid
flowchart LR; A[Technical Blog Post] --> B[AWS Marketplace Listing]; B --> C[Terraform Deployment Module]; C --> D[Zero-Egress Object Profile]; D --> E[Continuous Profiling Tier]; E --> F[Multi-VPC Container Fleet]; F --> G[AWS Bedrock Tool Registry];
```

## Startup Proof Points

_Illustrative — target and order-of-magnitude estimate figures, not an achieved track record (this Thing is concept-stage)._

**Pilot Goals**:
- A 14-day ad-hoc profiling pilot on a 10TB storage bucket designed to prove zero data egress and validate local compute overhead remains precisely proportional to scan volume.
- A 30-day continuous scanning deployment on a single high-volume AWS account aiming to process all new object writes and apply segmentation tags automatically without stalling data ingestion.
**Target Metrics**:
- Target: 0 bytes of payload data egressed from the host VPC during classification execution.
- Aim: 50% lower per-GB data classification cost compared to managed AWS Macie pricing.
- Target: 100% of local scan execution compute isolated to customer-owned ephemeral Spot instances or serverless functions.
**Target Case Studies**:
- Mid-sized healthcare software provider mapping 100TB of unstructured S3 bucket data via local execution to identify PHI without triggering third-party HIPAA vendor access reviews.
- Enterprise security operations team tracking PII distribution across 50 distinct cloud accounts by deploying serverless profiling containers directly into their own VPCs.
- SaaS data engineering pipeline implementing continuous event-driven tagging on newly written cloud objects to categorize 10TB of monthly volume at under 5 cents per GB.
**Testimonial Targets**:
- Healthcare CISO validating that the zero-egress architecture completely bypassed the need for a lengthy vendor data sub-processor compliance audit.
- Head of Cloud Infrastructure praising the Terraform module for provisioning tightly scoped read-only access without granting broad IAM permissions to external tools.
- Data Privacy Officer confirming the exact identification of misclassified PII buckets utilizing customizable segmentation heuristics running on local infrastructure.

## Startup Top Risks

**Risks**:
- Severity: existential · Description: AWS Macie slashes per-GB scanning prices to near zero, neutralizing the core consumption-pricing advantage. · Mitigation Status: unmitigated
- Severity: high · Description: Enterprise security teams refuse to grant the extensive IAM roles required to deploy the profiling engine directly inside their VPCs. · Mitigation Status: in-progress
- Severity: high · Description: Unoptimized scanning algorithms cause severe compute billing spikes within the customer's own cloud environment. · Mitigation Status: unmitigated
- Severity: moderate · Description: Complexity of supporting bespoke VPC networking configurations delays deployment and increases onboarding friction. · Mitigation Status: in-progress

## Startup Competitors

- [AWS Macie](/Competitors/AWS_Macie) — Incumbent AWS Service
- [Varonis](/Competitors/Varonis) — Enterprise Security Platform
- [Custom Python Scripts](/Competitors/Custom_Python_Scripts) — Status Quo DIY
- [Symmetry Systems](/Competitors/Symmetry_Systems) — Data Security Posture
- [Nightfall AI](/Competitors/Nightfall_AI) — Cloud Native DLP
- [Laminar Security](/Competitors/Laminar_Security) — Cloud Data Security

## Startup Solution Stack

- [Storage Profiling Engine](/Services/Storage_Profiling_Engine) — Service-as-Software
- [VPC Discovery Agent](/Agents/VPC_Discovery_Agent) — Agent
- [Object Segmentation Agent](/Agents/Object_Segmentation_Agent) — Agent
- [Local Execution API](/Software/Local_Execution_API) — Software
- [Consumption Billing SDK](/Software/Consumption_Billing_SDK) — Software

## Startup Story Brand

**Hero**:
- **Need**: to be the defender of patient privacy without compromising the cloud perimeter
- **Want**: to classify 100TB+ of unstructured bucket data for PII
- **Identity**: the security engineer at a healthcare software provider
**Plan**:
- Step: Deploy · Detail: Apply the scoped Terraform module to provision read-only, local compute in your own cloud account.
- Step: Approve · Detail: Verify the classification rules and bucket targets before the profiling engine begins sampling payloads.
- Step: Segment · Detail: Review the generated object metadata profiles to tag and secure PII across your distributed storage.
**Guide**:
- **Empathy**: You shouldn't still be manually auditing buckets via custom Python scripts. AWS Macie wasn't built to provide affordable, local-only segmentation for massive unstructured datasets.
**Problem**:
- **Villain**: data egress
- **External**: Profiling distributed S3 buckets in AWS Macie forces sensitive payload data out of your VPC and incurs high per-GB managed fees
- **Internal**: You feel like you are compromising HIPAA compliance just to understand what data you actually store
- **Philosophical**: Cloud storage was built for scale, not for holding data hostage behind premium classification fees.
**Success**: Every cloud object is classified and segmented by risk level, all while keeping your raw data strictly inside your VPC and your compute costs under control.
**One Liner**: The high cost of managed scanning costs healthcare providers their budget and their privacy. Characterizedisk profiles and segments distributed cloud objects inside your own VPC so you secure PII without data egress.
**Positioning**:
- **So That**: classify unstructured data at half the cost without triggering compliance risks
- **Unlike**: AWS Macie
- **For Whom**: security engineers at healthcare software providers
- **Category**: In-VPC data classification and profiling
**Call To Action**:
- **Direct**: Profile your buckets
- **Transitional**: Download classification schema
**Failure Stakes**:
- Unidentified PII remains exposed in forgotten storage buckets
- Managed service bills exceed your infrastructure budget
- Audit failures from vendor data-access violations
**Transformation**:
- **To**: the infrastructure's governance architect
- **From**: a security lead running fragile Python scripts
**Controlling Idea**: Data classification should happen where the data lives, not in a vendor's cloud.

## Startup Token Hero

**Genre**: founding-hypothesis
**Rendered**: The high cost of managed scanning costs healthcare providers their budget and their privacy. Characterizedisk profiles and segments distributed cloud objects inside your own VPC so you secure PII without data egress.
**Mechanism**: spine-derived-v1
**Template Id**: spine-founding-hypothesis
**Vocab Fingerprint**: 9c62ca57efaf9c84

## Startup Token Positioning

**Genre**: moore-positioning
**Rendered**: In-VPC data classification and profiling for security engineers at healthcare software providers. Unlike AWS Macie — classify unstructured data at half the cost without triggering compliance risks.
**Mechanism**: spine-derived-v1
**Template Id**: spine-moore-positioning
**Vocab Fingerprint**: a44a2aeebfe69e39

## Startup Token Pitch Deck

**Genre**: pitch-deck
**Rendered**: Problem: Profiling distributed S3 buckets in AWS Macie forces sensitive payload data out of your VPC and incurs high per-GB managed fees
Solution: The high cost of managed scanning costs healthcare providers their budget and their privacy. Characterizedisk profiles and segments distributed cloud objects inside your own VPC so you secure PII without data egress.
Customer: security engineers at healthcare software providers
Unlike: AWS Macie
**Mechanism**: spine-derived-v1
**Template Id**: spine-pitch-deck
**Vocab Fingerprint**: 52c1a470f15bdd61

## Startup Token M E D D P I C C

**Pain**: Profiling distributed S3 buckets in AWS Macie forces sensitive payload data out of your VPC and incurs high per-GB managed fees
**Metrics**: Target: Every cloud object is classified and segmented by risk level, all while keeping your raw data strictly inside your VPC and your compute costs under control.
**Rendered**: Pain: Profiling distributed S3 buckets in AWS Macie forces sensitive payload data out of your VPC and incurs high per-GB managed fees
Economic buyer: Cloud Infrastructure Engineer
Metrics: Target: Every cloud object is classified and segmented by risk level, all while keeping your raw data strictly inside your VPC and your compute costs under control.
Competition: AWS Macie
**Mechanism**: spine-derived-v1
**Competition**: AWS Macie
**Economic Buyer**: Cloud Infrastructure Engineer
**Vocab Fingerprint**: 1b54c0528d6f0da3

## Startup Token Cold Email

**Genre**: cold-email
**Rendered**: Subject: In-VPC data classification and profiling for security engineers at healthcare software providers

security engineers at healthcare software providers — Profiling distributed S3 buckets in AWS Macie forces sensitive payload data out of your VPC and incurs high per-GB managed fees The high cost of managed scanning costs healthcare providers their budget and their privacy. Characterizedisk profiles and segments distributed cloud objects inside your own VPC so you secure PII without data egress.
**Mechanism**: spine-derived-v1
**Template Id**: spine-cold-email
**Vocab Fingerprint**: b7cbf942e1da4fed

## Startup Token Agent Spec

**Genre**: ai-agent-spec
**Rendered**: In-VPC data classification and profiling. The high cost of managed scanning costs healthcare providers their budget and their privacy. Characterizedisk profiles and segments distributed cloud objects inside your own VPC so you secure PII without data egress. Serves security engineers at healthcare software providers.
**Mechanism**: spine-derived-v1
**Template Id**: spine-ai-agent-spec
**Vocab Fingerprint**: e84dfa88e0b9e44b

## Neighborhood

### Candidate solutions

- [Bioinformatics Talent Sourcing](/Problems/Bioinformatics_Talent_Sourcing) — candidate solution for · Problems

### What it offers

- [VPC Storage Profiler](/Software/VPC_Storage_Profiler) — offers · Software

### Composed of

- [Local Execution API](/Software/Local_Execution_API) — composes · Software
- [Object Segmentation Agent](/Agents/Object_Segmentation_Agent) — composes · Agents
- [Consumption Billing SDK](/Software/Consumption_Billing_SDK) — composes · Software
- [Storage Profiling Engine](/Services/Storage_Profiling_Engine) — composes · Services
- [VPC Discovery Agent](/Agents/VPC_Discovery_Agent) — composes · Agents

### Embodies

- [Software](/Theses/Software) — embodies · Theses

### Competitors

- [AWS Macie](/Competitors/AWS_Macie) — competes with · Competitors
- [Varonis](/Competitors/Varonis) — competes with · Competitors
- [Laminar Security](/Competitors/Laminar_Security) — competes with · Competitors
- [Nightfall AI](/Competitors/Nightfall_AI) — competes with · Competitors
- [Custom Python Scripts](/Competitors/Custom_Python_Scripts) — competes with · Competitors
- [Symmetry Systems](/Competitors/Symmetry_Systems) — competes with · Competitors

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