Cut Obsolete Tools

Discover, Relate, and Monitor Quality - with Agentic AI

Instantly uncover hidden relationships and safeguard data quality—no prep, no code, just plug-and-play Agentic AI

See Agentic AI in action

Challenges in discovery, relations and quality

Meet the Solution

Manual workload

Autonomous reasoning graphs

Time-consuming, unreliable manual processes for finding and understanding metadata across static data dictionaries.

Auto-generated trusted metadata with business context

Undocumented Relationships

Real-Time Context Intelligence

Lack of context and poor mapping of data relationships, dependencies, and lineage, which complicates decision-making.

Relationship Inferencing and Lineage graphs

Quality & Compliance Gaps

Instant Answers

Difficulty in tracking real-time data quality, and ensuring compliance (e.g., PII).

AI-powered privacy detection and tagging

Outdated Data

Multi-Persona Agents

Poor visibility into data freshness, null values, and unannounced schema changes can compromise the integrity of reports and metrics.

Always-current schema and quality monitoring

Features

Intuitive workflow with full human control and transparency.

Discover Metadata Catalog Flexibly

Chat

Keyword Search

PII

Filter

Tag management

Profiling

Column-Level Stats

Relationships and Lineage

Joins

Dependencies

Primary keys

Foreign keys

Lineage

Medallion layers

Data Quality Monitoring

Data Profiling

Column-Level Statistics

Missing Values

Object state

Auto-generated documentation with versioning

Dictionary

Descriptions

Semantic enrichment

Object state

Access Control

Data workspace

Teams

Roles

Encrypted context

Trusted data sharing

Discover Metadata Catalog Flexibly

Chat

Keyword Search

PII

Filter

Tag management

Profiling

Column-Level Stats

Relationships and Lineage

Joins

Dependencies

Primary keys

Foreign keys

Lineage

Medallion layers

Data Quality Monitoring

Data Profiling

Column-Level Statistics

Missing Values

Object state

Auto-generated documentation with versioning

Dictionary

Descriptions

Semantic enrichment

Object state

Access Control

Data workspace

Teams

Roles

Encrypted context

Trusted data sharing

The Connecty AI Difference: Trust at its core

01. Deep Context Learning

Real-Time Context intelligence gives autonomous data agents the ability to understand, adapt to, and act on ever-changing structured data systems

02. Dynamic Semantic Layer

Connects the semantics with context with a powerful interactive visualization - no manual creation or maintenance of semantic layer required.

03. Flexible Search and Interaction

Flexibility to search, chat, or filter, allowing you to tailor workflows and depth of analysis to your needs.

04. Relationship Intelligence

Weave relationships based on data lineage, query history, business context, and statistical key deduction.

05. Seamless Collaboration

Facilitate collaboration across teams—analysts, engineers, and compliance officers—using shared governance policies and tools to ensure consistency and efficiency.

Case studies

Logistics

How many SKUs were in stock yesterday?

What is the orders funnel for the last 6 months, including creation time, planned shipping time, picking duration, loading time, shipping confirmation, canceled orders, release duration, and finished orders?

How many SKUs were in stock yesterday?

What is the orders funnel for the last 6 months, including creation time, planned shipping time, picking duration, loading time, shipping confirmation, canceled orders, release duration, and finished orders?

B2C SaaS

Compare the churn rate for users acquired through paid ads vs. organic in the last quarter — and show how it correlates with engagement levels.

How does churn behavior differ across user cohorts based on signup month, and what role do product usage frequency play in early vs late-stage churn?

Show the subscription acquisition funnel over the past 6 months: site

Compare the churn rate for users acquired through paid ads vs. organic in the last quarter — and show how it correlates with engagement levels.

How does churn behavior differ across user cohorts based on signup month, and what role do product usage frequency play in early vs late-stage churn?

Show the subscription acquisition funnel over the past 6 months: site

E-commerce:

Which page with the country US had the highest increase compared to the previews week on march first 2025

Which page in the gaming playground category has the highest total clicks? how many impressions did the most clicked page in the gaming playground reach?

Which page with the country US had the highest increase compared to the previews week on march first 2025

Which page in the gaming playground category has the highest total clicks? how many impressions did the most clicked page in the gaming playground reach?