Software Alternatives & Startups

CodeinCloud VS G8KEPR

Compare CodeinCloud VS G8KEPR and see what are their differences

CodeinCloud

CodeinCloud is the comprehensive IDE on the cloud by which you can connect your Live Servers through SSH Connection and your hosting directories with FTP access and Enjoy the Live Developments with beautifully designed code :)

Rating
0 reviews
G8KEPR

Unified security for APIs, AI agents, MCP tools, and LLM applications. API Security + MCP Security + AI Gateway + Verification Engine. Starting at $399/mo.

Rating
0 reviews
Pricing
Freemium Free trial $399 / Monthly (API Security - MCP Security - AI Gateway - Verification Engine)

Base details

Website, pricing, platforms and company facts side by side.

CodeinCloud
G8KEPR
Website codeincloud.net g8kepr.com
Pricing
Freemium Free trial $399 / Monthly (API Security - MCP Security - AI Gateway - Verification Engine) Official pricing
Platforms —
SaaS Cloud Self Hosted REST API Docker Kubernetes Linux +4
Company — Startup from the United States · 1 - 9 employees · 2026
Listed in —

About CodeinCloud and G8KEPR

In their own words, as submitted to SaaSHub.

CodeinCloud
G8KEPR

No description of CodeinCloud yet.

A runtime security layer for AI apps — API, MCP, gateway, and model-output checks on one request plane, running inside your own VPC. Not a human at a keyboard — an AI agent running a multi-stage campaign: a recon probe, a fuzzing burst, a prompt injection, a poisoned tool. Each move rides below...

Read more about G8KEPR

Features and specs

What each product offers, as listed by its team.

CodeinCloud 5 features
G8KEPR 7 features
  • Cloud-based development
    CodeinCloud offers a cloud-based coding environment, allowing developers to write, run, and manage code from anywhere without needing to set up a local development environment.
  • Accessibility
    Being web-based, the platform can be accessed from various devices and locations, making it convenient for remote work and collaboration across teams.
  • No local setup required
    Users can start coding quickly without installing IDEs, compilers, or dependencies on their own machines, which lowers the barrier to entry for beginners.
  • Potential for collaboration
    Cloud platforms often support real-time collaboration features, enabling multiple developers to work together on the same codebase efficiently.
  • Scalability
    Cloud infrastructure can typically scale resources up or down based on project needs, which is helpful for handling varying workloads.

Possible disadvantages

  • Internet dependency
    As a cloud-based service, it requires a stable internet connection to function, which can be a limitation in areas with poor connectivity or during outages.
  • Limited information available
    There is relatively little publicly available detail about the platform's specific features, pricing, and reliability, making it harder to evaluate thoroughly.
  • Data privacy concerns
    Storing code and projects on a third-party cloud raises potential security and privacy considerations, especially for sensitive or proprietary projects.
  • Potential performance limitations
    Cloud-based environments may experience latency or performance constraints compared to a powerful local development setup, depending on the service tier.
  • Vendor lock-in
    Relying on a specific cloud platform may make it difficult to migrate projects elsewhere, creating dependency on the provider's continued operation and pricing.
  • API Security
    1,500+ threat signatures, OWASP Top 10 coverage, real-time anomaly detection
  • MCP Security
    Deterministic tool-poisoning & rug-pull detection (SHA-256), CVE replay
  • AI Gateway
    Inline LLM firewall across 14+ providers, prompt + response scanning
  • Deterministic detection
    Regex + classical ML, ~7ms, $0 per token, no LLM-as-judge
  • Verification Engine
    Output DLP — PII/secret redaction plus grounding/hallucination checks
  • Deployment
    Runs in your VPC — zero data egress, self-hostable
  • Frameworks
    Mapped to OWASP, MITRE ATT&CK, ATLAS, and EU AI Act

Analysis

An editorial look at what each product does well and who it suits.

CodeinCloud
G8KEPR

Overall verdict

  • I don't have verified, up-to-date information about CodeinCloud (codeincloud.net) to confidently assess its quality, reliability, or reputation. I cannot find reliable details about its features, pricing, user reviews, or business legitimacy in my training data, and I'm unable to browse the internet to check current information.

Why this product is good

  • Insufficient verified information available about this specific service to make reliability claims
  • No confirmed data on user reviews, uptime, customer support quality, or pricing structure
  • Cannot verify company legitimacy, ownership, or how long it has been operating
  • Unable to confirm security practices, data handling policies, or compliance certifications

Recommended for

  • Not able to provide a recommendation without additional verified information
  • Suggest checking independent review sites like Trustpilot, G2, or Reddit for user experiences
  • Consider verifying through domain registration lookups (e.g., WHOIS) for company transparency
  • Look for verifiable customer testimonials, uptime guarantees, and clear refund/support policies before committing
  • If considering this service, test with a small trial or free tier first if available before committing to a paid plan

No analysis of G8KEPR yet.

Questions & Answers

As answered by people managing CodeinCloud and G8KEPR.

What's the story behind your product?

G8KEPR's answer:

G8KEPR started from a simple observation: every AI security tool assumed you were fine sending your prompts to someone else's cloud to be inspected — and none of them covered the new attack surface that MCP and AI agents introduced.

So it was built the opposite way: deterministic detection that runs inside your own network, covering all four layers of the modern AI stack, with honest, reproducible benchmarks instead of marketing numbers.

What makes your product unique?

G8KEPR's answer:

Most AI security tools use an LLM to judge whether input is an attack — which is slow, costs per token, and is itself jailbreakable.

G8KEPR does the opposite:

  • Deterministic detection (regex + classical ML) — ~7ms, $0 per token, no LLM-as-judge
  • Runs in your own VPC — zero data egress, works air-gapped
  • Dedicated MCP security — deterministic tool-poisoning & rug-pull detection, with replay tests for real MCP CVEs (the part almost no one else covers)

Why should a person choose your product over its competitors?

G8KEPR's answer:

Four security layers in one platform — API Security, MCP Security, AI Gateway, and a Verification Engine — instead of stitching together separate vendors.

  • Legacy gateways (Kong, Apigee) were built before LLMs, agents, and MCP existed, and charge $20k+/yr for middleware
  • G8KEPR starts at $399/month with AI-native capabilities they don't offer
  • Detection is deterministic and reproducible — published benchmarks, including the weak spots
  • Nothing leaves your network

How would you describe the primary audience of your product?

G8KEPR's answer:

Engineering and security teams shipping AI applications to production — anyone running LLMs, AI agents, or MCP tools.

Especially:

  • Teams that can't send prompts to a third-party cloud for analysis (privacy, compliance, air-gapped)
  • Teams securing the agent tool-call layer (MCP), not just the API
  • Teams preparing for EU AI Act enforcement

Which are the primary technologies used for building your product?

G8KEPR's answer:

Frontend: Next.js, React, TypeScript, Tailwind CSS Backend: Python, FastAPI, PostgreSQL, Redis Detection: self-hosted classical ML (TF-IDF + logistic regression) and fine-tuned models — no hosted LLM in the detection path Billing: Stripe Deployment: Linux / nginx, containerized for VPC & self-hosted

Who are some of the biggest customers of your product?

G8KEPR's answer:

Newly launched — early access is open at g8kepr.com.

User comments

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