Enterprise-Ready Agentic Data Engineers

Q: How is Genesis different from AI coding assistants like Cursor?

Cursor suggests and writes code snippets which you review and execute. Genesis researches context, inspects and understands data, maps data from the source, generates and runs data pipeline code, documents, creates and runs data pipeline tests, and monitors—all ambiently. Think of it as hiring a junior data engineer vs. installing autocomplete.

Q: What tasks can Genesis Data Agents perform?

Genesis Data Agents perform: 1) Data Engineering - Build data pipelines from scratch, migrate legacy SAP/Oracle systems, automate data transformation code development, maintain and update data catalogs, generate data quality tests. 2) Data Operations - Monitor pipelines 24/7, diagnose and fix pipeline failures automatically, optimize warehouse performance, detect security anomalies, post results to Slack/Teams/Jira. 3) Business Analysis - Convert natural language questions into SQL, generate visualizations and dashboards, perform ad-hoc data analysis, create automated reports.

Q: Where does my data actually go?

With Snowflake Native App, Genesis agents run using Snowpark Container Services inside your Snowflake account. Your data NEVER leaves your Snowflake environment. Genesis Computing Inc. CANNOT see your data, conversations, or agent metadata. Only you control data access to the application through Snowflake's permissions.

Q: Do Genesis agents learn and improve over time?

Yes! Genesis agents build a knowledge base from your conversations, learn your team's patterns and preferences, optimize their own workflows based on feedback, remember context from past tasks, and continuously expand their capabilities.

Q: Can multiple agents work together?

Absolutely. Genesis uses multi-agent orchestration with specialized agents for different roles (Engineering, QA, Analysis). Agents break down complex tasks and delegate to specialists. Eve (the 'mother agent') creates and manages other custom agents. Agents communicate and coordinate on complex projects and can work concurrently on tasks.

Q: What tools and platforms do Genesis agents work with?

Genesis agents work with Data Platforms (Snowflake, Databricks, Amazon AWS, Azure), Orchestration tools (dbt, Dagster, Airflow), Communication platforms (Slack, Microsoft Teams, Email, Google Sheets, Docs, Jira, Git), and AI Models (Snowflake Cortex, ChatGPT, Amazon Bedrock, Claude, Grok, Gemini).

Genesis provides highly skilled pre-trained AI data agents securely running inside your enterprise, using your existing tools and methods, and accelerating your data engineering team from day one.

Try It Now

Request a Demo

what we do

Efficiently Automate Data Workflows

Watch Demo

Technology

February 27, 2026

The Same Four Engineers. 3–5x the Output.

When a major acquisition tripled GrowthZone's migration backlog, Director of Data Services Chandler Klose passed on a $400k hiring plan and chose Genesis instead.

20 days → 1 day

Reduced SDLC friction

3-5x

Migration capacity increase

$300–450K

Hiring plan avoided

For Hedge Funds

Investment

December 29, 2025

Multi-Agent Processing of Alternative Data Feeds

A New York-based hedge fund replaced bespoke ingestion with a multi-agent pipeline, reducing manual work and handling schema changes.

For Hedge Funds

60–70%

Reduction in human-written code

3-5 days

Faster time-to-signal for new feeds

~$200K annually

Data engineer headcount avoidance

Banking

August 14, 2025

The Future of Data Engineering: From Months to Hours with Agentic AI

GXS Bank cut data pipeline development from months to hours using Genesis Agents on Snowflake.

95%

Reduced SDLC friction

400+ hrs

Freed time from manual work

3 mo → 5 hrs

Delivery cycle compression

In the Media

Our CEO Joined the Podcast

How Data Engineers Are “10x’ing” Themselves With Agents

View Episode

Deployments

Platform-Agnostic AI Data Engineering

Choose environment and deploy our autonomous AI Agents wherever your data engineering happens. Genesis integrates natively with your existing data stack.

learn more

how it works

From Data Context to Automated
Pipeline Execution

Onboard agents with Context

Connect agents to your stack & build a Context Graph

During onboarding, Genesis agents connect to your repositories, databases, and tools to map data flows and capture team knowledge in a Context Graph.

Identify & Define Blueprints

Choose or create a blueprint for your data workflow

Select a Blueprint that matches your use case or create one to define the workflow, including flexible steps, conditions, and early exits.

Automate Tasks with Missions

Align agents and humans around aclear mission

Define the goal, scope, and success criteria. Missions coordinate agents and people while tasks verify each step and keep work aligned.

Alt: Genesis platform interface showing an enterprise context graph with connected data tools such as Snowflake, Informatica, Databricks, PowerBI, Tableau, and Git.

Genesis blueprint interface displaying a source-to-target mapping workflow with documentation files, processing phases, and generated outputs connected in a visual flow.

Genesis missions dashboard showing multiple active data tasks with progress bars, including data integrity audit, analytics pipeline, and requirements documentation.

Onboard agents with Context

Identify & Define Blueprints

Automate Tasks with Missions

integrations

Work With Your Entire Data Stack

Gensesis agents connect to and orchestrate data across all your systems. Genesis integrates with any data warehouse, ETL framework, app, or API — Snowflake, BigQuery, Redshift, Azure Fabric, Databricks, dbt, Airflow, Jira, GitHub, and beyond.

testimonials

Trusted for Complex AI Data Use Cases

I brought up my data warehouse concept and started typing to Genesis in natural language: here's the schema I have in mind, here's the GitHub repo, start building this.
Genesis was rolling out commit after commit on that repo. Two hours later I was done. I had the prototype for the data warehouse. I said: this is the tool we're going to use.

Chandler Klose

Director of Data Services

Genesis is helping us automate routine work across our core data team while unlocking the hidden data workforce across the business.
For certain workflows, Genesis has helped us complete data tasks up to 40x faster.”

Fortune 100

Pharmaceutical Company

We are dealing with the ramifications of the Iran conflict, which has required ingesting a significant amount of new data — with speed of access being critical. We would not have been able to do it without Genesis. It's brought tangible value during a time of great need.

Top NYC Financial Company

Hedge Fund

As a digital-first bank, our mission is to make banking better for everyday consumers and small businesses. Leveraging Genesis Data Agents, GXS will be able to bring products to market faster for our customers by reducing our data development cycle from what would’ve taken months to hours.

Harikrishnan Raguraman

Head of Enterprise Technology, GXS Bank

Over the past year, AI agents have gone from unheard of to one of the key building blocks to increasing AI productivity and unlock insights that deliver real business value. Genesis Computing’s founders have taken advantage of this opportunity by building their autonomous data agents natively on the Snowflake AI Data Cloud, enabling them to accelerate adoption through instant access to thousands of enterprises that depend on the security and governance of the Snowflake platform.

Christian Kleinerman

EVP of Product, Snowflake

We’re seeing the demand for intelligent automation in enterprise data workflows skyrocket over the past two years. Genesis Computing’s autonomous data agents deliver precisely what these enterprises need: scalable, production-ready AI knowledge workers that boost productivity and ROI. Matt and Justin are incredible entrepreneurs and have their fingers on the pulse of what these large enterprises need having worked at stellar organizations in the past.

Sriram Krishnan

Managing Partner at Kearny Jackson

The modern data stack unlocked unprecedented scale and efficiency for organizations, but the next step will be making AI a first-class participant in agentic enterprise workflows. By leveraging AI Agents, Genesis is enabling businesses to automate their complex data operations. I believe their approach represents the next big shift in the data space.

Bob Muglia

Former Snowflake CEO

Frequently Asked
Questions

What is Genesis?

Genesis is an agentic system that powers AI data workers to execute complete data workflows from start to finish—not AI assistants that just suggest code. Genesis agents research data sources, ingest data, map data from bronze source to gold targets , write code, create documentation, test data pipelines, commit git PRs, monitor pipelines and fix errors while learning from your environment.

How is Genesis different from AI coding assistants like Cursor?

Cursor – Suggests and writes code snippets (which is the easy part)→ you review → you execute
Genesis – Researches context → inspects and understands data → maps data from the source → generate and runs data pipeline code → documents → creates and runs data pipeline tests → monitors—all ambiently. Think of it as hiring a junior data engineer vs. installing autocomplete.

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Read the full breakdown of how we are different here

What's the difference between Genesis and my existing data tools?

Traditional Stack
‍

Fivetran for ingestion
dbt for transformation
Airflow for orchestration
Monte Carlo for monitoring

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Genesis Agents
‍

One autonomous agent platform that uses all of the tools in your existing stack

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Genesis augments human data engineers, connects to and uses the traditional tools, and fits right into your existing data engineering / pipeline building / CI/CD process with agents that handle the entire workflow.

Do Genesis agents replace my data team?

No. Genesis agents handle repetitive, undifferentiated work (source to target mapping, pipeline maintenance, monitoring, catalog updates) so your team can focus on strategic work (architecture, ML models, business analysis). Think "augmentation" not "replacement."

What are my options for trying Genesis?

There are two deployment paths based on your needs:

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Option 1: Enterprise Production (Snowflake Native App)

Best for: Production use with sensitive data
Setup: Install from Snowflake Marketplace (one click)
Runs on: Inside YOUR Snowflake account
Data access: Your Snowflake data (Genesis never sees it)
Use case: Full-scale automation, production pipelines
Security: Enterprise-grade, Snowflake RBAC, data never leaves your environment

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Option 2: Container Deployment (Advanced)

Best for: VPC, Custom on-premise deployments or other cloud platforms ( AWS, Azure)
Setup: Docker-based installation, AWS Elastic Kubernetes Service cluster, Azure Kubernetes Service cluster
Contact: support@genesiscomputing.ai to schedule a call with the solution engineer.

What tasks can Genesis Data Agents perform?

1. Data Engineering

Build data pipelines from scratch
Migrate legacy SAP/Oracle systems
Automate data transformation code development
Maintain and update data catalogs
Generate data quality tests

‍

2. Data Operations

Monitor pipelines 24/7 (Dagster, dbt, Airflow)
Diagnose and fix pipeline failures automatically
Optimize warehouse performance
Detect security anomalies (unusual access patterns, over-provisioned roles)
Post results to Slack/Teams/Jira

‍

3. Business Analysis

Convert natural language questions into SQL
Generate visualizations and dashboards
Perform ad-hoc data analysis
Create automated reports

What tools and platforms do Genesis agents work with?

Data Platforms:

Snowflake (native)
Databricks
Amazon
AWS
Azure

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Orchestration:

dbt
Dagster
Airflow

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Communication:

Slack, Microsoft Teams, Email
Google Sheets, Docs, Jira, Git, others

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AI Models:

Snowflake Cortex
ChatGPT
Amazon Bedrock
Claude
Grok
Gemini

Do Genesis agents learn and improve over time?

Yes! Genesis agents:

Build a knowledge base from your conversations
Learn your team's patterns and preferences
Optimize their own workflows based on feedback
Remember context from past tasks
Continuously expand their capabilities

Can multiple agents work together?

Absolutely. Genesis uses multi-agent orchestration:

Specialized agents for different roles (Engineering, QA, Analysis)
Agents break down complex tasks and delegate to specialists
Eve (the "mother agent") creates and manages other custom agents
Agents communicate and coordinate on complex projects
Agents can work concurrently on tasks

Where does my data actually go?

With Snowflake Native App:

Genesis agents run inside your Snowflake account using Snowpark Container Services
Your data NEVER leaves your Snowflake environment
Genesis Computing Inc. CANNOT see your data, conversations, or agent metadata
Only you control data access to the application through Snowflake's permissions

What information CAN Genesis Computing see?

Only in Snowflake Native App:

Your Snowflake account name
Email address of the person who installed the app
Optional: Application event logs if you explicitly enable log sharing

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Genesis CANNOT see:

Your data
Your agent conversations
Agent configurations or additional application data
Any business logic or queries

What if I can't use external LLMs like OpenAI?

No problem! When installed as a Snowflake Native App, Genesis uses Snowflake Cortex models by default—no data ever leaves your Snowflake environment. Coming soon: Amazon Bedrock support.

Can I test Genesis without connecting real data?

Absolutely! Genesis includes:

Pre-loaded Baseball and Formula 1 demo datasets
Access to Snowflake Marketplace public datasets
Upload your own non-sensitive test data

Is Genesis SOC 2 compliant? What about HIPAA/GDPR?

Genesis leverages your existing Snowflake compliance posture. If your Snowflake environment is SOC 2/HIPAA/GDPR compliant, Genesis inherits those controls by running natively inside your account.