Software Alternatives & Startups

G8KEPR VS SQL Chat

Compare G8KEPR VS SQL Chat and see what are their differences

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)
SQL Chat

Chat-based SQL Client and Editor for the next decade

Rating
0 reviews
Pricing
Open source

Which is more popular?

API Gateway popularity
100% vs 0%
alternatives listed
24 vs 86

Base details

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

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

About G8KEPR and SQL Chat

In their own words, as submitted to SaaSHub.

G8KEPR
SQL Chat

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

No description of SQL Chat yet.

Features and specs

What each product offers, as listed by its team.

G8KEPR 7 features
SQL Chat 4 features
  • 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
  • User-Friendly Interface
    SQL Chat offers an intuitive and easy-to-use interface, making it accessible for users with varying levels of SQL knowledge to engage in database querying without extensive training.
  • AI-Powered Assistance
    The platform leverages artificial intelligence to help users write SQL queries efficiently, providing suggestions and corrections as needed, which can significantly speed up the querying process.
  • Real-Time Collaboration
    SQL Chat allows for real-time collaboration, enabling multiple users to work together on SQL queries simultaneously, which can enhance productivity and collaborative problem-solving.
  • Cross-Platform Compatibility
    The service can be accessed from various devices and operating systems, making it a versatile tool for users who are on the go or working in different environments.

Possible disadvantages

  • Limited Advanced Features
    While SQL Chat is beneficial for standard queries, it may lack some advanced features needed by experienced developers or analysts requiring more complex database interactions.
  • Dependency on Internet Connection
    The platform requires an active internet connection, which could be a limitation for users in areas with unreliable connectivity or when working in offline environments.
  • Potential Privacy Concerns
    Using an online platform for querying databases may raise privacy and security concerns, especially for sensitive data, as it involves uploading query data to the platform's servers.
  • Learning Curve for New Features
    As with any software, new updates and features could introduce a learning curve, requiring users to adapt and learn how to use them effectively, which might temporarily slow down their workflow.

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
G8KEPR
SQL Chat
100% 100%
0% 0%
22% 22%
AI
78% 78%
100% 100%
API
0% 0%
0% 0%
100% 100%

Questions & Answers

As answered by people managing G8KEPR and SQL Chat.

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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Alternatives to G8KEPR and SQL Chat

When comparing G8KEPR and SQL Chat, you can also consider the following products.