| What it does | The data layer for AI agents
| Semantic context layer that helps AI agents understand your business data accurately
|
|---|
| Stage | Startup
| MVP
|
|---|
| Founded | 2026
| Not given
|
|---|
| Based in | US
| Not given
|
|---|
| Pricing model | Paid
| Not given
|
|---|
| Pricing | Base: $50/mo for 50,000 points per month. Core: $100/mo for 100,000 points per month. Pro: $250/mo for 250,000 points per month. Ultima: $500/mo for 500,000 points per month. Enterprise: $1000/mo for 1,000,000 points per month. Custom option available for higher volumes. Search costs 5 points per ca
| Not given
|
|---|
| Key features | - AI research for structured, cited answers across sources
- AI extraction converts pages to clean JSON without selectors
- 250+ data sources including company registries and business intelligence
- MCP server integration with Claude, OpenAI, and other clients
- REST API for custom agent code
- Web search capability for AI agents
- Points-based pricing model with no per-source fees
- AI research depth tiers from quick lookups to exhaustive investigations
| - 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 | - Unified API and MCP access to 250+ data sources without stitching scrapers
- Structured, cited answers synthesized from comprehensive source catalog
- No HTML parsing or selector maintenance required for extraction
- One request format for all company intelligence and registry sources
- Points reset monthly with no per-source pricing complexity
| - 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 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) | 4 ▲ +3 (up) since last check | 8 ● no change since last check |
|---|
| Trust Flow (Majestic) | 1 | 1 |
|---|
| Citation Flow (Majestic) | 27 | 24 |
|---|
| Referring domains (Majestic) | 61 | 29 |
|---|
NeuralVerge
Kanlet