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85puntuación
HN · front_page
SaaS subscription
Build

Refusal-aware AI router for security teams

Build a multi-model security assistant that routes defensive tasks to the best available model based on refusal likelihood, cost, and past task success. The main value is reliability: users can submit triage, audit, and API-testing prompts once and get the highest chance of a usable answer without manually bouncing between vendors.

5 canalesTendencia de menciones de 30 días: latest 0, peak 4, 30-day series
Ver en Reddit
Descubierto 15 ago 2026

Por qué es importante

You are trying to use AI to investigate a bug, review suspicious code, or test an API, but the experience is unpredictable. One model refuses the task, another works but is expensive, and a third is accessible only through a different provider. Even after jumping through approval steps, you still do not know whether the prompt will be accepted. So you keep multiple accounts open, rewrite prompts manually, and waste time rerunning the same job. What you want is not a more powerful model in theory. You want a dependable layer that gets legitimate security work done with the least friction and the lowest token spend.

  • · Creado para Small security teams, independent security researchers, and developer-led infrastructure teams performing code review, vulnerability triage, and API security testing..
  • · Monetización más probable: SaaS subscription.

El Dolor · Narrativa

You are trying to use AI to investigate a bug, review suspicious code, or test an API, but the experience is unpredictable. One model refuses the task, another works but is expensive, and a third is accessible only through a different provider. Even after jumping through approval steps, you still do not know whether the prompt will be accepted. So you keep multiple accounts open, rewrite prompts manually, and waste time rerunning the same job. What you want is not a more powerful model in theory. You want a dependable layer that gets legitimate security work done with the least friction and the lowest token spend.

Desglose de puntuación

Intensidad del dolor10/10
Disposición a pagar8/10
Facilidad de construcción4/10
Sostenibilidad7/10

Señal de Mercado

Tendencia de menciones de 30 díasPico: 4
Sparkline: latest 0, peak 4, 30-day series
Canales cubiertos
front_pageNousResearch/hermes-agentproductivityanomalyco/opencodeselfhosted

Estrategia de lanzamiento

Usuario objetivo exacto

Independent security researchers and 2-20 person application security teams already paying for at least two model providers.

Número estimado de usuarios

~30K-80K active global early adopters

Canal de adquisición principal

Twitter dev community

Ancla de precio

$79/month

Primer hito

25 paying users who connect two or more model providers and run 200+ routed jobs in 30 days

Alcance del MVP · 1-2 semanas

Semana 1
  • Implement a simple web UI for submitting security-related prompts with redaction warnings
  • Connect three model backends through direct APIs or a unified gateway
  • Create a rule-based router that tags prompts as triage, audit, or API testing
  • Log refusal outcomes, latency, and cost per request in PostgreSQL
  • Build a manual fallback chain that retries the next model after refusal
Semana 2
  • Add a dashboard showing success rate, refusal rate, and cost by model and task type
  • Implement prompt rewriting suggestions to preserve defensive framing
  • Create reusable templates for common workflows such as issue triage and code audit
  • Add API keys, team workspaces, and basic usage metering
  • Launch a concierge beta to 10 security-heavy users and collect routed job data
Funciones MVP: Prompt classification for benign defensive workflows · Automatic model routing based on refusal history and cost · Fallback chain across multiple model providers · Audit logs showing why a request was rerouted or blocked · Task templates for code audit, issue triage, and API testing

Diferenciación

Soluciones existentes
OpenAIAnthropicKimi K3GLMDwarfStar
Nuestro enfoque
There is no trusted software layer that combines real-world model benchmarking, refusal-aware routing, compliance documentation, and cost control specifically for coding and defensive security workflows.

Por qué esto podría fallar

Autorrefutación: la señal de confianza más importante

  1. 1Model vendors may tighten terms or block patterns that look like refusal circumvention, limiting product usefulness.
  2. 2Users with sensitive code may refuse to send security prompts through a new intermediary unless on-prem or strict privacy options exist.
  3. 3If major vendors improve legitimate security access quickly, the routing pain may shrink before the product gains distribution.

Resumen de evidencia

Cómo la IA sintetizó esta información: sin citas textuales

Discussion participants repeatedly described abandoning one model for another because defensive security tasks were blocked or inconsistently allowed. Roughly a dozen comments centered on refusals, approvals, or the need to switch providers for triage, auditing, and API testing. Several also mentioned cost tradeoffs, showing that a router optimizing both task completion and spend would solve an active workflow problem rather than a hypothetical one.

1 1 publicación analizada5 5 canalesAI · Sintetizado por IA · sin citas textuales

Plan de Acción

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Kit de Textos para Landing Page

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Titular

Refusal-aware AI router for security teams

Subtítulo

Build a multi-model security assistant that routes defensive tasks to the best available model based on refusal likelihood, cost, and past task success. The main value is reliability: users can submit triage, audit, and API-testing prompts once and get the highest chance of a usable answer without manually bouncing between vendors.

Para Quién Es

Para Small security teams, independent security researchers, and developer-led infrastructure teams performing code review, vulnerability triage, and API security testing.

Lista de Funciones

✓ Prompt classification for benign defensive workflows ✓ Automatic model routing based on refusal history and cost ✓ Fallback chain across multiple model providers ✓ Audit logs showing why a request was rerouted or blocked ✓ Task templates for code audit, issue triage, and API testing

Dónde Validar

Comparte tu landing page en r/HN · front_page — ahí es exactamente donde se descubrieron estos puntos de dolor.

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Preguntas frecuentes

¿Quién siente este problema?
Small security teams, independent security researchers, and developer-led infrastructure teams performing code review, vulnerability triage, and API security testing.
¿Es esta una oportunidad real?
Esta oportunidad tiene una puntuación de 85/100 en la métrica compuesta de Pain Spotter (intensidad del dolor, disposición a pagar, viabilidad técnica y sostenibilidad). Valídala más a fondo antes de dedicar tiempo de ingeniería.
¿Cómo debería validarla?
Realiza 5 conversaciones de descubrimiento de clientes con el público objetivo, publica una landing page con lista de espera y revisa la publicación de origen enlazada para ver la actividad reciente antes de desarrollar.