The Mission
Why iqtoolkit Exists
Built from a decade of real Database professional pain — not theoretical use cases.
The Problem
After more than a decade of manually diagnosing slow queries, building monitoring dashboards, and tuning database performance in production environments, it became clear: database teams are drowning in metrics but starving for actionable intelligence.
Existing tools surface raw data — wait events, query plans, lock chains — but leave the interpretation entirely to you. Every incident means hours of context switching between dashboards, documentation, and tribal knowledge. That cost scales poorly and burns out senior engineers.
The Solution
iqtoolkit was created to solve real production challenges — bringing AI-powered insights to database operations without cloud dependencies, vendor lock-in, or privacy compromises. Every feature is built from actual Database professional pain points.
No cloud dependencies
Runs entirely on-prem via Docker or Kubernetes. Your query data never leaves your infrastructure.
No vendor lock-in
Open-source core with support for PostgreSQL, MongoDB, and more on the roadmap.
Privacy first
Local LLM inference via Ollama means sensitive schema and query data stays internal.
The Vision
Make AI-powered database intelligence accessible to every operations team — regardless of budget, cloud provider, or infrastructure complexity.
Whether you're running a single Postgres instance on a $10 VPS or a 200-node Kubernetes cluster, iqtoolkit should give your team the same diagnostic power that previously required a dedicated DBA with 10+ years of experience.
Ready to see it in action?
Meet the creator, explore the roadmap, or jump straight into the docs.