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NeuralTrust vs Kanlet

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

NeuralTrust compared with Kanlet
DetailNeuralTrust logo NeuralTrustKanlet logo Kanlet
What it doesSecurity platform for governing and protecting enterprise AI agents Semantic context layer that helps AI agents understand your business data accurately
StageNot given MVP
FoundedNot given Not given
Based inES Not given
Pricing modelNot given Not given
PricingFree plan: $0/month with 100,000 requests/month. Standard plan: $49/month with $49 usage credit included and $0.0003 per request beyond included credit. Enterprise plan: Custom pricing with committed volume and discounts. Additional features priced separately: Smart routing at $0.0002 per execution, Not given
Key features
  • Agent Posture Management
  • AI Red Teaming
  • Prompt injection protection
  • Multi-turn injection protection
  • PII & secret detection
  • <100 ms latency real-time enforcement
  • On-premise, SaaS, or hybrid deployment
  • Split-plane architecture for data sovereignty
  • 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
What makes it different
  • Handles 20K+ requests per second per node with linear scaling
  • Unified policy enforcement across homegrown, third-party SaaS, and endpoint deployments without custom integration work
  • 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
Free planNot given Not given
Open sourceNot given Not given
PlatformsNot given Not given
Public APINot given Not given
Community votes00
DR (Domain Rating by Ahrefs)60 no change since last check8 no change since last check
Trust Flow (Majestic)151
Citation Flow (Majestic)4224
Referring domains (Majestic)118629

3 details filled in for both companies.

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