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85puntuación
HN · front_page
SaaS subscription
Build

Privacy-first AI code gateway

Build a secure routing layer for coding AI that lets teams choose models without exposing sensitive source code to unintended training or retention. The product would provide provider-level policy enforcement, redaction, audit logs, and selective routing between low-cost and privacy-safe models.

En aumento +122%5 canalesTendencia de menciones de 30 días: latest 0, peak 4, 30-day series
Ver en Reddit
Descubierto 6 ago 2026

Por qué es importante

You want to use AI coding tools across real repositories, but every request feels like a policy gamble. One pricing tier is cheap because your data may help train future models, another has unclear retention terms, and login-gated tools make you wonder what is being logged behind the scenes. If you work on customer code, internal systems, or regulated data, you cannot casually paste code into whichever model is cheapest that week. What you need is a simple way to keep shipping with AI while enforcing rules about what leaves your environment, which providers are allowed, and what proof exists afterward.

  • · Creado para Software teams, security-conscious startups, and SMB engineering orgs that want AI coding assistance but need clear control over data retention and provider usage..
  • · Monetización más probable: SaaS subscription.

El Dolor · Narrativa

You want to use AI coding tools across real repositories, but every request feels like a policy gamble. One pricing tier is cheap because your data may help train future models, another has unclear retention terms, and login-gated tools make you wonder what is being logged behind the scenes. If you work on customer code, internal systems, or regulated data, you cannot casually paste code into whichever model is cheapest that week. What you need is a simple way to keep shipping with AI while enforcing rules about what leaves your environment, which providers are allowed, and what proof exists afterward.

Desglose de puntuación

Intensidad del dolor9/10
Disposición a pagar8/10
Facilidad de construcción4/10
Sostenibilidad8/10

Señal de Mercado

Tendencia de menciones de 30 díasPico: 4
Sparkline: latest 0, peak 4, 30-day series
Canales cubiertos
front_pagecodexproductivitycontinuedev/continuedeveloper-tools

Estrategia de lanzamiento

Usuario objetivo exacto

Engineering managers at startups with 10-100 developers who already reimburse AI coding tools but lack a formal data policy.

Número estimado de usuarios

~50K teams globally

Canal de adquisición principal

Twitter dev community

Ancla de precio

$99/month

Primer hito

10 paying teams and at least 3 using policy-based routing on active repositories within 30 days

Alcance del MVP · 1-2 semanas

Semana 1
  • Build a simple proxy API that forwards prompts to two model providers with request logging
  • Add repository-level policy settings for allowed providers and retention preference
  • Implement basic secret and PII redaction on prompt payloads
  • Create a minimal web dashboard showing request history and provider used
  • Ship a CLI wrapper that routes coding prompts through the proxy
Semana 2
  • Add rule-based routing by folder, file type, or sensitivity tag
  • Integrate one IDE extension surface such as VS Code command palette actions
  • Create vendor policy comparison pages inside the dashboard
  • Add team accounts, API keys, and Stripe billing
  • Run pilots with 5 design partners and collect blocked-request and routed-request metrics
Funciones MVP: Prompt and code redaction before provider calls · Policy-based model routing by repository or file sensitivity · Audit logs showing where data was sent and under what retention setting · Vendor policy registry comparing training, retention, and region behavior · CLI and IDE plugin for drop-in usage

Diferenciación

Soluciones existentes
DeepSeekOpenAI Codex CLIClaude CodeGoogle Gemini CLI
Nuestro enfoque
There is unmet demand for neutral tooling that helps developers adopt AI coding safely, compare vendors on real operating metrics, and deploy without consumer-account friction.

Por qué esto podría fallar

Autorrefutación: la señal de confianza más importante

  1. 1Teams may decide that direct use of one enterprise-grade provider is simpler than adopting a gateway.
  2. 2The product could become a compliance checkbox rather than a daily workflow tool, reducing perceived value.
  3. 3If vendors offer native zero-retention guarantees and audits broadly, the routing layer may feel unnecessary.

Resumen de evidencia

Cómo la IA sintetizó esta información: sin citas textuales

The discussion repeatedly returns to anxiety about prompt inspection, code upload, and low-cost tiers that rely on customer data reuse. Multiple commenters contrasted cheaper plans that permit training with alternatives that avoid retention, showing that privacy is not abstract but a purchasing criterion. Several participants also distrusted login-gated closed systems, which strengthens the case for a neutral control layer.

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

Plan de Acción

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Construir

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Titular

Privacy-first AI code gateway

Subtítulo

Build a secure routing layer for coding AI that lets teams choose models without exposing sensitive source code to unintended training or retention. The product would provide provider-level policy enforcement, redaction, audit logs, and selective routing between low-cost and privacy-safe models.

Para Quién Es

Para Software teams, security-conscious startups, and SMB engineering orgs that want AI coding assistance but need clear control over data retention and provider usage.

Lista de Funciones

✓ Prompt and code redaction before provider calls ✓ Policy-based model routing by repository or file sensitivity ✓ Audit logs showing where data was sent and under what retention setting ✓ Vendor policy registry comparing training, retention, and region behavior ✓ CLI and IDE plugin for drop-in usage

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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Report & PRDBUSINESS

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Preguntas frecuentes

¿Quién siente este problema?
Software teams, security-conscious startups, and SMB engineering orgs that want AI coding assistance but need clear control over data retention and provider usage.
¿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.