IdeaWell

Project ideas from Hacker News discussions.

Launch HN: Consus (YC F24) – LLM gateway for companies handling sensitive data

Hacker News Discussion

📝 Discussion Summary (Click to expand)

Three prevalent themes in the discussion

  1. Data‑privacy guarantees and contractual safeguards
  2. Users want assurance that proprietary or CUI data never leaks to model training or third parties.
  3. runamuck: “Will this guarantee that proprietary/ sensitive/ CUI data won't leak to model training or other parties?”

  4. ericmags: “Correct. We have contractual agreements to ensure no data that passes through our platform will be used for model training purposes. In addition, we have in our contracts that we (Consus) will also not use any data for training purposes. We couldn't if we wanted to since we do not store any prompt data.”

  5. Guidance and tool‑level controls for AI‑assisted workflows (MCP, plugins, web‑search, etc.)

  6. Commenters ask how the gateway manages the tools that AI agents invoke and what controls are offered to organizations.
  7. projectescape: “Do you give customers guidance or controls for that side, or is it out of scope for the gateway?”
  8. ericmags: “We do give our customers guidance to make sure they are thinking about this properly. This typically happens during on‑boarding. We also built out pre‑defined controls for common tools so they can click a button and not think about it.”

  9. projectescape (suggestion): “You could strip non‑approved tools from the request and block calls to them in the response, based on an org allowlist.”

  10. Compliance, security monitoring, and regulator‑aligned controls (HIPAA, FedRAMP, abuse detection)

  11. Concerns about meeting specific compliance regimes and how the gateway handles provider‑side abuse monitoring or data retention.
  12. jayonsoftware: “Does this work with HIPAA data ?”
  13. ericmags: “We've been focused on defense, so we haven't set up HIPAA (BAAs) yet. The underlying controls are essentially FedRAMP High, so it wouldn't be a big lift on our side.”
  14. ericmags (abuse monitoring): “The infra providers call this 'abuse monitoring' or 'abuse detection' and we've worked with them to turn it off. … We have one case remaining for OpenAI's GPT‑5.x models in AWS. AWS's automated classifier can retain a flagged request for up to 30 days. … We are actively working to turn that off as well.”

These three themes—privacy guarantees, tool‑level governance, and compliance/security controls—dominated the conversation.

🚀 Project Ideas

Generating project ideas…

ConsusGuard Data Isolation Gateway

Summary

  • A reverse‑proxy gateway that guarantees all prompts and responses are never stored, never used for model training, and are covered by enforceable contracts with model providers.
  • Core value proposition: zero‑data‑retention assurance for proprietary, sensitive, or CUI data when using any LLM service.

Details

Key Value
Target Audience Enterprises handling regulated or confidential data (defense, finance, healthcare) that use AI coding agents or LLM APIs
Core Feature Real‑time interception, enforcement of no‑log/no‑train policies, automatic contract‑compliance attestation, and immutable audit trails
Tech Stack Go/Rust high‑performance proxy, Envoy sidecar, OAuth2/OIDC for auth, PostgreSQL for audit logs, WebAssembly plugins for policy
Difficulty Medium
Monetization Revenue-ready: tiered subscription based on monthly processed tokens (e.g., $0.0005 per 1K tokens)

Notes

  • Addresses runamuck’s concern: “Will this guarantee that proprietary/ sensitive/ CUI data won't leak to model training or other parties?” and ericmags’ reply about contractual guarantees and no data storage.
  • Provides the missing piece ericmags mentioned: turning off abuse‑monitoring retention and offering verifiable proof for auditors and customers.

MCP Policy Enforcer

Summary

  • A centralized policy engine that inspects every Model‑Context‑Protocol (MCP) tool call, strips non‑approved tools, and blocks disallowed calls based on an organization‑wide allowlist.
  • Core value proposition: eliminates the risk of uncontrolled tool usage by AI coding agents while keeping the developer experience seamless.

Details

Key Value
Target Audience Development teams using Claude Code, Codex, or similar AI agents that rely on MCP servers, plugins, or web‑search/fetch
Core Feature Dynamic allowlist/blocklist for MCP tool schemas, automatic stripping of disallowed tools from requests, blocking of corresponding responses, and real‑time policy change propagation
Tech Stack TypeScript/Node.js plugin framework, Redis for fast policy lookup, gRPC for agent communication, OpenAPI schemas for tool definitions, Docker‑based sidecar deployment
Difficulty Medium
Monetization Revenue-ready: per‑seat SaaS pricing (e.g., $12/user/month) with free tier for open‑source projects

Notes

  • Directly implements projectescape’s suggestion: “You could strip non‑approved tools from the request and block calls to them in the response, based on an org allowlist.”
  • Extends ericmags’ existing controls (tool schema blocking, URL flagging) to a full MCP‑focused firewall that HN commenters would appreciate for its precision and zero‑touch developer workflow.

AI App Compliance Scanner (Rowly‑style for HIPAA/FedRAMP)

Summary

  • An automated testing suite that signs into AI‑powered applications, exercises APIs, storage, and database rules, then generates a compliance report against HIPAA, FedRAMP, or custom security baselines.
  • Core value proposition: continuous verification that AI‑built apps meet regulatory controls without manual pen‑testing.

Details

Key Value
Target Audience DevOps, security, and compliance teams building or deploying AI‑enabled services that must satisfy HIPAA, FedRAMP, or similar frameworks
Core Feature Scripted flows (sign‑in, API calls, storage checks, DB rule validation) using headless browsers, automated evidence collection, and pass/fail reporting integrated into CI/CD pipelines
Tech Stack Python (Playwright/Selenium), Docker for isolated test environments, OpenPolicyAgent for rule definitions, JSON/HTML reports, optional integration with GitHub Actions/GitLab CI
Difficulty Low
Monetization Hobby (open‑source core) with optional paid support/enterprise add‑ons

Notes

  • Builds on popkoren’s tool rowly.me, extending it to HIPAA/FedRAMP specifics that ericmags noted are “essentially FedRAMP High” and would need BAAs.
  • Provides the practical utility skinfaxi asked for in a crowded space: a focused, automated compliance checker that HN users can adopt and discuss for improving trust in AI‑generated applications.

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