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SQL Chat VS G8KEPR

Compare SQL Chat VS G8KEPR and see what are their differences

SQL Chat

Chat-based SQL Client and Editor for the next decade

Rating
0 reviews
Pricing
Open source
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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)
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KeptPDF
Redact, edit, OCR, and sign PDFs entirely in your browser. The file never leaves your device. Free, no account needed. sponsored

Which is more popular?

AI popularity
78% vs 22%
alternatives listed
86 vs 24

Base details

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

SQL Chat
G8KEPR
Website sqlchat.ai g8kepr.com
Pricing
Open source
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
Utilities Communications GPT Tools MySQL Tools Online Services AI +3
Cyber Security AI MCP API LLM Gateway API Gateway Security & Privacy Monitoring Tools Security API Tools +7

About SQL Chat and G8KEPR

In their own words, as submitted to SaaSHub.

SQL Chat
G8KEPR

No description of SQL Chat 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.

SQL Chat 4 features
G8KEPR 7 features
  • 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.
  • 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

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
SQL Chat
G8KEPR
78% 78%
AI
22% 22%
0% 0%
API Gateway
100% 100%
100% 100%
MySQL Tools
0% 0%
0% 0%
API
100% 100%

Questions & Answers

As answered by people managing SQL Chat 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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Alternatives to SQL Chat and G8KEPR

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