# Forgescreen

*/Startups/Forgescreen*

## Startup Overview

This platform executes continuous digital vetting by cross-referencing real-time threat intelligence feeds against active user sessions and transactions. It replaces static background checks and periodic reviews with an active surveillance layer that evaluates risk at every digital touchpoint.

Digital platforms and financial networks face the constant threat of illicit actors slipping past point-in-time verification checks. When businesses rely on manual compliance analysts, they suffer from delayed onboarding and missed threat vectors. This system eliminates manual review backlogs by automating the detection of sanctioned entities, fraudulent networks, and compromised accounts the moment a digital footprint shifts.

Legacy fraud and compliance tools like Chainalysis and Sift output probabilistic scoring models that require human interpretation and create alert fatigue. This engine operates on fully deterministic logic, delivering binary, policy-enforcing decisions based strictly on hard threat data. Paired with an outcome-priced billing structure, the platform charges exclusively for conclusive security resolutions, removing the financial burden of ambiguous risk scores.

## Startup Founding Hypothesis

**Approach**: that cross-references threat intelligence feeds for continuous digital vetting
**Competitors**:
- [Manual Compliance Analysts](/Competitors/Manual_Compliance_Analysts)
- [Chainalysis](/Competitors/Chainalysis)
- [Sift](/Competitors/Sift)
**Differentiator2x2**: fully deterministic and outcome-priced rather than relying on probabilistic scoring models

## Startup Solution Coordinate

**Solution**: [Deterministic Vetting Engine](/Services/Deterministic_Vetting_Engine)

## Startup Position2x2

```mermaid
quadrantChart; title Digital Vetting Positioning; x-axis Probabilistic Scoring --> Fully Deterministic; y-axis Effort/SaaS Priced --> Outcome-Priced; Forgescreen: [0.85, 0.85]; Manual Compliance Analysts: [0.95, 0.15]; Chainalysis: [0.65, 0.40]; Sift: [0.15, 0.25]
```

## Startup Customer Journey

```mermaid
flowchart LR; A[Identity Orchestration Marketplace] --> B[Shadow-Mode Sandbox]; B --> C[Deterministic Vetting Endpoint]; C --> D[Outcome Billing Node]; D --> E[Continuous Monitoring Engine]; E --> F[Autonomous Risk Agent]; F --> G[Threat Intelligence Network];
```

## 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 shadow-mode parallel run processing 10,000 transactions to prove deterministic clear or block accuracy against the incumbent probabilistic vendor.
- 14-day API latency test simulating peak volume spikes to validate sub-300ms response times and test the negotiated monthly billing cap.
**Target Metrics**:
- Target: 0 percent false positive rate on known threat feeds
- Aim: 80 percent reduction in manual compliance review queues
- Target: sub-300ms API response latency for real-time transaction vetting
- Aim: 100 percent deterministic outcomes where inconclusive queries incur zero cost
**Target Case Studies**:
- Mid-market payment gateway Risk Manager: Cut manual review queues by 80 percent by replacing probabilistic scoring with deterministic clear or block outcomes.
- Early-stage digital asset exchange Compliance Lead: Achieved zero false positives on known threat feeds, enabling transaction volume scaling without adding manual compliance headcount.
- Established fintech app Head of Operations: Validated vendor switch via a 30-day shadow-mode pilot, proving sub-300ms latency and 100 percent conclusive vetting under the monthly billing cap.
**Testimonial Targets**:
- Head of Risk at a digital asset platform: Sentiment must highlight that the deterministic clear or block guarantee eliminated the gray-area alerts drowning their analyst team.
- Compliance Director at a payment gateway: Sentiment must confirm that shadow-mode testing safely proved Forgescreen's accuracy against a legacy vendor without cutover risk.
- VP of Engineering at an early-stage fintech: Sentiment must emphasize that the pay-per-outcome model and sub-300ms API made integration fast and predictable during volume spikes.

## Startup Top Risks

**Risks**:
- Severity: existential · Description: Major threat intelligence providers revoke API access or restrict commercial usage of their feeds. · Mitigation Status: unmitigated
- Severity: high · Description: The outcome-based pricing model creates severe revenue volatility or SLA liabilities if the deterministic engine misses novel threat vectors. · Mitigation Status: in-progress
- Severity: moderate · Description: Strictly deterministic rules fail to catch rapidly mutating fraud tactics compared to competitors utilizing probabilistic machine learning. · Mitigation Status: in-progress
- Severity: moderate · Description: New data privacy regulations restrict the legal aggregation and processing of cross-border threat intelligence indicators. · Mitigation Status: unmitigated

## Startup Competitors

- [Manual Compliance Analysts](/Competitors/Manual_Compliance_Analysts) — Status Quo
- [Chainalysis](/Competitors/Chainalysis) — Incumbent Vetting
- [Sift](/Competitors/Sift) — Probabilistic Scoring
- [Socure](/Competitors/Socure) — Identity Risk Platform
- [Alloy](/Competitors/Alloy) — Decision Engine

## Startup Token Hero

**Genre**: founding-hypothesis
**Rendered**: What if every security check was a definitive yes or no? Forgescreen cross-references real-time threat feeds to deliver deterministic vetting that eliminates compliance guesswork.
**Mechanism**: spine-derived-v1
**Template Id**: spine-founding-hypothesis
**Vocab Fingerprint**: f64875d0b78de8aa

## Startup Token Positioning

**Genre**: moore-positioning
**Rendered**: Continuous Digital Vetting Platform for compliance leads at digital platforms. Unlike probabilistic models like Sift — eliminate manual review backlogs with deterministic binary decisions.
**Mechanism**: spine-derived-v1
**Template Id**: spine-moore-positioning
**Vocab Fingerprint**: cd80519f15be4f76

## Startup Token Pitch Deck

**Genre**: pitch-deck
**Rendered**: Problem: Sift and Chainalysis generate ambiguous risk scores that force compliance analysts to manually adjudicate thousands of flags every week
Solution: What if every security check was a definitive yes or no? Forgescreen cross-references real-time threat feeds to deliver deterministic vetting that eliminates compliance guesswork.
Customer: compliance leads at digital platforms
Unlike: probabilistic models like Sift
**Mechanism**: spine-derived-v1
**Template Id**: spine-pitch-deck
**Vocab Fingerprint**: c0e974a4780da973

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

**Pain**: Sift and Chainalysis generate ambiguous risk scores that force compliance analysts to manually adjudicate thousands of flags every week
**Metrics**: Target: Your platform runs on a continuous vetting layer that blocks threats instantly, leaving only the most complex cases for your human experts.
**Rendered**: Pain: Sift and Chainalysis generate ambiguous risk scores that force compliance analysts to manually adjudicate thousands of flags every week
Economic buyer: Fintech Compliance Teams
Metrics: Target: Your platform runs on a continuous vetting layer that blocks threats instantly, leaving only the most complex cases for your human experts.
Competition: probabilistic models like Sift
**Mechanism**: spine-derived-v1
**Competition**: probabilistic models like Sift
**Economic Buyer**: Fintech Compliance Teams
**Vocab Fingerprint**: f67bf524632de9aa

## Startup Token Cold Email

**Genre**: cold-email
**Rendered**: Subject: Continuous Digital Vetting Platform for compliance leads at digital platforms

compliance leads at digital platforms — Sift and Chainalysis generate ambiguous risk scores that force compliance analysts to manually adjudicate thousands of flags every week What if every security check was a definitive yes or no? Forgescreen cross-references real-time threat feeds to deliver deterministic vetting that eliminates compliance guesswork.
**Mechanism**: spine-derived-v1
**Template Id**: spine-cold-email
**Vocab Fingerprint**: 7374b56ad9757101

## Startup Token Agent Spec

**Genre**: ai-agent-spec
**Rendered**: Continuous Digital Vetting Platform. What if every security check was a definitive yes or no? Forgescreen cross-references real-time threat feeds to deliver deterministic vetting that eliminates compliance guesswork. Serves compliance leads at digital platforms.
**Mechanism**: spine-derived-v1
**Template Id**: spine-ai-agent-spec
**Vocab Fingerprint**: ca49a768618f15f1

## Neighborhood

### Candidate solutions

- [Reconcile Synthetic Ledgers](/Problems/Reconcile_Synthetic_Ledgers) — candidate solution for · Problems

### What it offers

- [Deterministic Vetting Engine](/Services/Deterministic_Vetting_Engine) — offers · Services

### Composed of

- [Deterministic Vetting Service](/Services/Deterministic_Vetting_Service) — composes · Services
- [Threat Intelligence Agent](/Agents/Threat_Intelligence_Agent) — composes · Agents
- [Cross-Reference Worker](/Agents/Cross-Reference_Worker) — composes · Agents
- [Deterministic Rules Engine](/Agents/Deterministic_Rules_Engine) — composes · Agents
- [Threat Feed API](/Agents/Threat_Feed_API) — composes · Agents

### Embodies

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

### Competitors

- [Manual Compliance Analysts](/Competitors/Manual_Compliance_Analysts) — competes with · Competitors
- [Chainalysis](/Competitors/Chainalysis) — competes with · Competitors
- [Sift](/Competitors/Sift) — competes with · Competitors
- [Socure](/Competitors/Socure) — competes with · Competitors
- [Alloy](/Competitors/Alloy) — competes with · Competitors

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