# Wholoblem

*/Startups/Wholoblem*

## Startup Overview

This autonomous incident resolution engine maps cross-system dependencies to isolate the root causes of infrastructure outages. When critical services fail, the system bypasses the alert flood to trace the exact fault origin across microservices, network layers, and databases.

Legacy monitoring and paging setups force on-call engineers into manual log parsing, acting as mere notification systems that leave the actual debugging to humans. This alternative executes the entire diagnostic and remediation workflow entirely on its own. Organizations pay strictly per resolved incident rather than by seat or ingested data volume, tying the cost explicitly to restored functionality.

## Startup Founding Hypothesis

**Approach**: that maps cross-system dependencies to isolate root causes
**Competitors**:
- [Datadog](/Competitors/Datadog)
- [PagerDuty](/Competitors/PagerDuty)
- [Manual Log Parsing](/Competitors/Manual_Log_Parsing)
**Differentiator2x2**: fully autonomous in execution and priced per resolved incident

## Startup Solution Coordinate

**Solution**: [AutoSRE Agent](/Agents/AutoSRE_Agent)

## Startup Position2x2

```mermaid
quadrantChart
    title Market Positioning: Wholoblem vs Competitors
    x-axis Manual Execution --> Fully Autonomous Execution
    y-axis Fixed or Usage Pricing --> Priced per Resolved Incident
    quadrant-1 Autonomous & Value-Based
    quadrant-2 Manual & Value-Based
    quadrant-3 Manual & Fixed Price
    quadrant-4 Autonomous & Fixed Price
    Manual Log Parsing: [0.15, 0.15]
    PagerDuty: [0.45, 0.20]
    Datadog: [0.65, 0.25]
    Wholoblem: [0.90, 0.85]
```

## Startup Offer

**Proof**:
- Targeting engineering teams aiming to reduce Mean Time To Resolution (MTTR) from hours to minutes.
- Designed to achieve 90% accuracy in isolating root causes across distributed cloud environments.
- Aiming to autonomously resolve standard P3 alerts with zero human intervention required.
**Tiers**:
- Name: Runbook Generation · Price: ~$40–$90 per mapped incident · Inclusions: Automated root cause isolation, cross-system dependency mapping, and a generated remediation runbook delivered to the engineering team.
- Name: Autonomous Resolution · Price: ~$150–$300 per resolved incident · Inclusions: Direct API-driven remediation execution, post-fix health validation, and continuous monitoring until the alert clears for P1 and P2 incidents.
**Guarantee**: If the platform cannot successfully isolate the root cause and map the cross-system dependency within 15 minutes of the initial alert, the incident analysis is not billed.
**Business Function**: ProvideService
**Objection Handlers**:
- Objection: We already pay for Datadog and PagerDuty. Rebuttal: Those tools surface the symptoms and wake up your team; Wholoblem is designed to consume those alerts, find the root cause, and fix it.
- Objection: We cannot give an external system write-access to our production infrastructure. Rebuttal: The platform is designed to operate in a 'dry-run' mode, generating pull requests or Terraform plans for human approval before any autonomous execution.
- Objection: Paying per incident means our bill spikes when our systems are failing. Rebuttal: Accounts are designed with configurable monthly spend caps and burst limits to ensure predictable budgeting during cascading outages.
**Pricing Architecture**: UsageMeter
**Agent Checkout Support**:
- agentic-commerce-protocol

## Startup Brand

**Voice**: Clinical technical register driven by absolute diagnostic precision.
**Tagline**: Autonomous root cause isolation priced by the resolved incident.
**Icon Concept**: server
**Palette Intent**: electric-signal
**Visual Identity**: High-contrast terminal greens and absolute black anchor the palette, paired with dense monospace typography that mirrors raw system logs.
**Archetype Reference**: the-sage

## Startup Buyer Chain

**Chain**: Wholoblem -> VP Engineering -> On-Call SRE Teams
**Gtm Motion**: Acquires customers through a risk-free pilot where companies only pay per successfully resolved incident, lowering the barrier for initial adoption. Expands by starting on lower-tier staging environments or specific microservices, then moving laterally into tier-1 production systems as the autonomous dependency mapping builds trust.
**Agent Channel**: Designed for listing in the LangChain tool registry and autonomous DevOps capability feeds, allowing broader infrastructure agents to discover and invoke the dependency mapping capability during active incidents.
**Primary Channel**: SREs actively searching the AWS Marketplace and intended PagerDuty Integration Directory for MTTR reduction tools and automated root cause capabilities following major operational outages.

## Startup Customer Journey

```mermaid
flowchart LR; A[AWS Marketplace Listing] --> B[Dry-Run Mode Agent]; B --> C[Dependency Mapping Runbook]; C --> D[Staging Microservices]; D --> E[Tier-1 Production Systems]; E --> F[Autonomous Remediation API]; F --> G[Agentic DevOps Feed];
```

## Startup Proof Points

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

**Pilot Goals**:
- 30-day read-only shadow pilot connected to existing PagerDuty alerts, aiming to successfully isolate the root cause within 15 minutes for at least 80 percent of triggered incidents.
- 60-day dry-run deployment on a single staging microservice, targeting the generation of 10 perfectly mapped remediation Terraform plans requiring only a single human click to execute.
**Target Metrics**:
- Target: Under 15-minute root cause isolation and dependency mapping for inbound monitoring alerts.
- Aim: 90 percent accuracy in isolating root causes across distributed cloud environments.
- Target: 100 percent autonomous resolution of standard P3 alerts without human intervention.
**Target Case Studies**:
- Mid-market SaaS VP of Engineering shifting from manual debugging of cascading microservice failures to automated cross-system dependency mapping, minimizing engineer pager fatigue.
- Enterprise FinTech SRE Director transitioning from hour-long incident bridge calls to approving pre-generated Terraform remediation plans for P2 incidents.
- High-growth E-commerce DevOps Lead replacing manual post-mortem documentation with instant, auto-generated remediation runbooks during peak traffic database connection spikes.
**Testimonial Targets**:
- SRE Manager confirming that the dry-run mode generating pull requests built necessary internal trust before enabling full autonomous execution.
- VP of Engineering praising the predictable budgeting provided by configurable monthly spend caps during a cascading system outage.
- On-call DevOps Engineer expressing relief that the automated runbook generation bypassed the need to manually cross-reference Datadog logs at 3 AM.

## Startup Top Risks

**Risks**:
- Severity: existential · Description: The autonomous execution engine applies a destructive fix to a false positive, causing a major production outage for a customer. · Mitigation Status: in-progress
- Severity: high · Description: Observability incumbents like Datadog restrict or heavily monetize their APIs, blinding the cross-system dependency mapping engine. · Mitigation Status: unmitigated
- Severity: high · Description: Customers dispute the definition of a resolved incident under the per-resolution pricing model, leading to delayed payments and revenue churn. · Mitigation Status: in-progress
- Severity: moderate · Description: Enterprise security teams block the extensive infrastructure write permissions required for the platform to execute automated fixes. · Mitigation Status: unmitigated

## Startup Competitors

- [Datadog](/Competitors/Datadog) — Incumbent Observability
- [PagerDuty](/Competitors/PagerDuty) — Incident Management
- [Manual Log Parsing](/Competitors/Manual_Log_Parsing) — Status Quo
- [Dynatrace](/Competitors/Dynatrace) — Enterprise APM
- [BigPanda](/Competitors/BigPanda) — AIOps Platform

## Startup Story Brand

**Hero**:
- **Need**: to be the strategic architect of system resilience, not a human log-parser
- **Want**: to isolate the specific root cause of a P1 outage instantly
- **Identity**: on-call SRE leads at cloud-native software companies
**Plan**:
- Step: Define boundaries · Detail: Submit your infrastructure map and permission levels to establish safe dry-run or autonomous operating zones.
- Step: Inspect mappings · Detail: Review the automated dependency graph that isolates exactly where the signal chain broke during an incident.
- Step: Approve fixes · Detail: Approve the generated Terraform plan or remediation runbook to restore system health in minutes.
**Guide**:
- **Empathy**: When a service health check fails, the ensuing hunt through distributed traces often costs more in developer focus than the downtime itself.
**Problem**:
- **Villain**: alert fatigue
- **External**: When a P1 alert hits PagerDuty, engineers lose hours manually parsing raw Datadog logs and cross-referencing broken microservices to find one failed dependency.
- **Internal**: You feel the dread of a cascading failure while the Slack 'war room' demands an ETA you don't have.
- **Philosophical**: Every engineering team deserves diagnostic certainty — not a life spent chasing ghosts in the machine.
**Success**: Incidents reach resolution in minutes with automated root cause isolation and verified API-driven fixes.
**One Liner**: Manual log parsing costs engineering teams hours of downtime. Wholoblem isolates root causes and executes fixes autonomously so systems stay up without human intervention.
**Positioning**:
- **So That**: reduce MTTR from hours to minutes via automated root cause isolation
- **Unlike**: Manual log parsing and PagerDuty alerts
- **For Whom**: SRE leads at cloud-native companies
- **Category**: Autonomous Incident Remediation Platform
**Call To Action**:
- **Direct**: Resolve first incident
- **Transitional**: View sample remediation runbook
**Failure Stakes**:
- MTTR stretching into hours
- Developer burnout from midnight on-call shifts
- Revenue loss during uncontained cascading failures
**Transformation**:
- **To**: one of the few SRE leads who governs a self-healing infrastructure
- **From**: a tired engineer manual-parsing Datadog logs
**Controlling Idea**: Diagnostic precision should be autonomous and billed only when it works.

## Startup Token Hero

**Genre**: founding-hypothesis
**Rendered**: Manual log parsing costs engineering teams hours of downtime. Wholoblem isolates root causes and executes fixes autonomously so systems stay up without human intervention.
**Mechanism**: spine-derived-v1
**Template Id**: spine-founding-hypothesis
**Vocab Fingerprint**: 8d0c31a84efb864d

## Startup Token Positioning

**Genre**: moore-positioning
**Rendered**: Autonomous Incident Remediation Platform for SRE leads at cloud-native companies. Unlike Manual log parsing and PagerDuty alerts — reduce MTTR from hours to minutes via automated root cause isolation.
**Mechanism**: spine-derived-v1
**Template Id**: spine-moore-positioning
**Vocab Fingerprint**: 70bf3a64ca5b80fd

## Startup Token Pitch Deck

**Genre**: pitch-deck
**Rendered**: Problem: When a P1 alert hits PagerDuty, engineers lose hours manually parsing raw Datadog logs and cross-referencing broken microservices to find one failed dependency.
Solution: Manual log parsing costs engineering teams hours of downtime. Wholoblem isolates root causes and executes fixes autonomously so systems stay up without human intervention.
Customer: SRE leads at cloud-native companies
Unlike: Manual log parsing and PagerDuty alerts
**Mechanism**: spine-derived-v1
**Template Id**: spine-pitch-deck
**Vocab Fingerprint**: 641697562375a0fa

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

**Pain**: When a P1 alert hits PagerDuty, engineers lose hours manually parsing raw Datadog logs and cross-referencing broken microservices to find one failed dependency.
**Metrics**: Target: Incidents reach resolution in minutes with automated root cause isolation and verified API-driven fixes.
**Rendered**: Pain: When a P1 alert hits PagerDuty, engineers lose hours manually parsing raw Datadog logs and cross-referencing broken microservices to find one failed dependency.
Economic buyer: VP Engineering
Metrics: Target: Incidents reach resolution in minutes with automated root cause isolation and verified API-driven fixes.
Competition: Manual log parsing and PagerDuty alerts
**Mechanism**: spine-derived-v1
**Competition**: Manual log parsing and PagerDuty alerts
**Economic Buyer**: VP Engineering
**Vocab Fingerprint**: 06d500d0faded9ab

## Startup Token Cold Email

**Genre**: cold-email
**Rendered**: Subject: Autonomous Incident Remediation Platform for SRE leads at cloud-native companies

SRE leads at cloud-native companies — When a P1 alert hits PagerDuty, engineers lose hours manually parsing raw Datadog logs and cross-referencing broken microservices to find one failed dependency. Manual log parsing costs engineering teams hours of downtime. Wholoblem isolates root causes and executes fixes autonomously so systems stay up without human intervention.
**Mechanism**: spine-derived-v1
**Template Id**: spine-cold-email
**Vocab Fingerprint**: 7434bed5b3ff6272

## Startup Token Agent Spec

**Genre**: ai-agent-spec
**Rendered**: Autonomous Incident Remediation Platform. Manual log parsing costs engineering teams hours of downtime. Wholoblem isolates root causes and executes fixes autonomously so systems stay up without human intervention. Serves SRE leads at cloud-native companies.
**Mechanism**: spine-derived-v1
**Template Id**: spine-ai-agent-spec
**Vocab Fingerprint**: 83c40cddca0afa5e

## Neighborhood

### Candidate solutions

- [Integrated Competitor Margin Squeeze](/Problems/Integrated_Competitor_Margin_Squeeze) — candidate solution for · Problems

### Competitors

- [BigPanda](/Competitors/BigPanda) — competes with · Competitors
- [Datadog](/Competitors/Datadog) — competes with · Competitors
- [Dynatrace](/Competitors/Dynatrace) — competes with · Competitors
- [PagerDuty](/Competitors/PagerDuty) — competes with · Competitors
- [Manual Log Parsing](/Competitors/Manual_Log_Parsing) — competes with · Competitors
- [DVI Optical Software](/Competitors/DVI_Optical_Software) — competes with · Competitors
- [NetSuite ERP](/Competitors/NetSuite_ERP) — competes with · Competitors
- [Manual Spreadsheets](/Competitors/Manual_Spreadsheets) — competes with · Competitors
- [Epicor Prophet 21](/Competitors/Epicor_Prophet_21) — competes with · Competitors
- [Spreadsheet Margin Models](/Competitors/Spreadsheet_Margin_Models) — competes with · Competitors
- [manual spreadsheet models](/Competitors/manual_spreadsheet_models) — competes with · Competitors
- [Manual Spreadsheet Overrides](/Competitors/Manual_Spreadsheet_Overrides) — competes with · Competitors
- [Vistex](/Competitors/Vistex) — competes with · Competitors
- [Excel Spreadsheets](/Competitors/Excel_Spreadsheets) — competes with · Competitors
- [NetSuite](/Competitors/NetSuite) — competes with · Competitors
- [spreadsheet-based floor price calculations](/Competitors/spreadsheet-based_floor_price_calculations) — competes with · Competitors
- [Manual Quote Overrides](/Competitors/Manual_Quote_Overrides) — competes with · Competitors
- [NetSuite Pricing Modules](/Competitors/NetSuite_Pricing_Modules) — competes with · Competitors
- [Spreadsheet Price Models](/Competitors/Spreadsheet_Price_Models) — competes with · Competitors
- [Spreadsheet Models](/Competitors/Spreadsheet_Models) — competes with · Competitors
- [spreadsheet workarounds](/Competitors/spreadsheet_workarounds) — competes with · Competitors
- [Spreadsheet Quote Models](/Competitors/Spreadsheet_Quote_Models) — competes with · Competitors
- [Manual Excel Spreadsheets](/Competitors/Manual_Excel_Spreadsheets) — competes with · Competitors
- [spreadsheet pricing models](/Competitors/spreadsheet_pricing_models) — competes with · Competitors
- [NetSuite Static Pricing](/Competitors/NetSuite_Static_Pricing) — competes with · Competitors

### Embodies

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

### What it offers

- [AutoSRE Agent](/Agents/AutoSRE_Agent) — offers · Agents
- [Margin Prism](/Software/Margin_Prism) — offers · Software
- [Meridian Margin Graph](/Software/Meridian_Margin_Graph) — offers · Software

### Composed of

- [Voucher Extraction Engine](/Software/Voucher_Extraction_Engine) — composes · Software
- [Rebate Reconciliation Agent](/Agents/Rebate_Reconciliation_Agent) — composes · Agents
- [Bundle Ledger API](/Software/Bundle_Ledger_API) — composes · Software
- [Margin Allocation Service](/Services/Margin_Allocation_Service) — composes · Services
- [Meridian Pricing Agent](/Agents/Meridian_Pricing_Agent) — composes · Agents
- [Rebate Audit Agent](/Agents/Rebate_Audit_Agent) — composes · Agents
- [Focal Graph Engine](/Software/Focal_Graph_Engine) — composes · Software
- [Ledger Ingestion API](/Software/Ledger_Ingestion_API) — composes · Software
- [Lens Allocation Worker](/Agents/Lens_Allocation_Worker) — composes · Agents
- [Margin Calibration Service](/Services/Margin_Calibration_Service) — composes · Services

### Who it serves

- [Ophthalmic Goods Merchant Wholesalers](/CompanyTypes/Ophthalmic_Goods_Merchant_Wholesalers) — serves · CompanyTypes

### Similar Startups

- [Flarekeep](/Startups/Flarekeep) — similar · Startups
- [Outagyard](/Startups/Outagyard) — similar · Startups
- [Autoreman](/Startups/Autoreman) — similar · Startups
- [Astralagent](/Startups/Astralagent) — similar · Startups
- [Accit](/Startups/Accit) — similar · Startups
- [Stabamber](/Startups/Stabamber) — similar · Startups
- [Optel](/Startups/Optel) — similar · Startups
- [Problequency](/Startups/Problequency) — similar · Startups
- [Sentus](/Startups/Sentus) — similar · Startups
- [Accide](/Startups/Accide) — similar · Startups
- [Astroblem](/Startups/Astroblem) — similar · Startups
- [Actensity](/Startups/Actensity) — similar · Startups
- [Evorrelate](/Startups/Evorrelate) — similar · Startups
- [Autignal](/Startups/Autignal) — similar · Startups
- [Hoppermanor](/Startups/Hoppermanor) — similar · Startups
- [Autechanic](/Startups/Autechanic) — similar · Startups
- [Sen](/Startups/Sen) — similar · Startups
- [Triagehaven](/Startups/Triagehaven) — similar · Startups
- [Anomalyland](/Startups/Anomalyland) — similar · Startups
- [Action](/Startups/Action) — similar · Startups