Kanlet vs Context Engine

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Kanlet compared with Context Engine
Detail	Kanlet	Context Engine
What it does	Semantic context layer that helps AI agents understand your business data accurately	One memory for your AI agents and your team
Stage	MVP	Not given
Founded	Not given	Not given
Based in	Not given	Not given
Pricing model	Not given	Freemium
Pricing	Not given	Free: $0 forever with 1 agent per engine (up to 3 when friends refer), 1 GB memory. Pro: $12/month or $99/year per engine with 10 agents and 25 GB memory. Unlimited: $39/month or $299/year per engine with unlimited agents and 100 GB memory. Enterprise: from $6,000/year per install on your own server
Key features	Connects to 15+ data systems including Snowflake, Databricks, BigQuery, Redshift, dbt, Airflow, Tableau, Looker, Power BI and Postgres Extracts structural metadata including databases, schemas, tables, views, columns and relationship lineage Provides Web-UI, MCP server and REST APIs for accessing semantic context Automatic incremental updates with configurable sync schedules from on-demand to daily or weekly Role-level access controls and data classifications including PII, PHI and SPII Only reads metadata without accessing or moving actual data from systems Integrates with quality monitoring tools including Monte Carlo, Anomalo and Bigeye	Connect ChatGPT, Claude, Claude Code and Cursor with a few clicks AI tools save decisions, notes, people, customers and files Search with semantic understanding, not just exact words Automatic summaries by day, week and month Link related memories automatically Prevent duplicate memories with deduplication Export all data as Markdown and JSON Separate engines for clients with no data crossing Fine-grained access control (read or read-and-save) Full history tracking for every change
What makes it different	Eliminates confident AI mistakes by grounding agents in semantic context instead of having them guess from table names Reduces AI token costs and speeds up answers by resolving schema and joins once upstream instead of in each agent query Ensures consistent answers across all agents and teams using the same definitions and business logic Provides complete traceability and auditability of AI decisions with documented context and ownership	Keeps AI tools from forgetting context between sessions Data isolated per engine with no sharing between customers Fully portable—export anytime or delete permanently Pay per engine, never per person added to team
Free plan	Not given	Not given
Open source	Not given	Not given
Platforms	Not given	Not given
Public API	Not given	Not given
Community votes	0	0
DR (Domain Rating by Ahrefs)	8 no change since last check	15 +3 (up) since last check
Trust Flow (Majestic)	1	13
Citation Flow (Majestic)	24	28
Referring domains (Majestic)	29	32

3 details filled in for both companies.

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