Seolly vs Coginiti AI

Seolly is an analytics dashboard that pulls read-only Google Search Console data into one place for agencies managing many sites. You connect your GSC properties, see clicks and impressions across every domain on a single overview page, and drill into popular, growing, or decaying pages without clicking through Google's interface. It shows the same underlying numbers as Search Console, not traffic estimates from third-party crawlers.

Rank trackers and all-in-one SEO suites store your performance data on their servers. Seolly markets a privacy-first model where it does not store or resell your GSC metrics, only the Google OAuth key needed to render dashboards until you revoke access. Branded keyword filtering and custom content groups are built for client reporting where you need to strip branded queries or compare landing page clusters quickly.

SEO agencies, consultants, and affiliates with multiple Search Console properties are the core audience. Teams that export CSV reports for clients benefit from unlimited exports and a Privacy Blur mode that hides URLs in screenshots. Lifetime pricing at $49.99 targets freelancers who want to avoid another monthly subscription.

Writing and debugging SQL still eats hours even when the warehouse is fast, and Coginiti AI puts a conversational advisor inside the Coginiti analytics workspace to shorten that loop. You ask questions in plain language to catch syntax errors, get execution plan explanations, request sample queries, and tune joins or indexes without leaving the editor. The advisor learns from each interaction and stays optional, so teams can turn it off or point it at their own generative model.

Generic copilots draft text and stop. Coginiti AI stays inside a full SQL workbench with a personal analytics catalog, versioning, multi-database connections, and team sharing on higher tiers. Coginiti does not let third-party models touch your data platforms directly, which matters when you are querying production warehouses. Pro ships as a Windows or macOS desktop app with a 30-day free trial, while Team and Enterprise add shared catalogs, scheduling, and web deployment.

Data engineers, analysts, and scientists at security-conscious organizations use it to reuse SQL blocks, propagate code changes across dependent analytics, and cut compute costs from slower queries. Supported connections span major cloud warehouses plus Amazon S3, Azure Blob Storage, and Google Cloud Storage.