A direct path from insight to production

AI-assisted workbench designed to help data analysts and engineers build and operate data pipelines with less friction.
 
Connect the path from the initial business question to a reliable production asset with our unified collaborative environment.
 
 
Schedule discovery call
Register for live demo | Aug 21st
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Our vision

From analysis to operations

The handoff from data analysis to engineering is often slow and ambiguous. Analysts work to find an insight, and their findings, often delivered in static reports or dashboards, must be manually translated by engineers into production code. This process introduces delays and opportunities for misinterpretation.

On the other side, when production pipelines fail, engineers are pulled into reactive firefighting. They sift through logs and alerts to diagnose issues, a time-consuming process that puts business-critical decisions on hold and erodes trust in the data.

 

We create a more direct workflow for both roles.

We believe the solution lies in treating data as a portfolio of products

Not just in theory, but in a way that’s tied to real systems and workflows. That means connecting strategic thinking (value, cost, trust) to the actual technical implementation — whether that’s in Databricks, Starburst, Snowflake, or whatever else is in play.

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Explore Your Data Product Portal

We have all the tools you need to transform insight into confident, decisive action.

Centralized Products View

At-a-Glance Metrics

Automated Alert Feed

Deep-Dive Analysis

Actionable, Contextual Insights

Dependency Mapping

Automated Financials

Operational Readiness Score

Key Benefits

Human-in-the-loop AI

The AI agents handle tedious, repetitive tasks & exploration and leaves final review, approval, and complex problem-solving to the human experts.

Sandbox-first

Every proposed change is rigorously tested and validated in an isolated environment, ensuring that any solution is correct and safe to deploy.

Integrates with your tools

The Agentic Data Workbench connects with your existing tools, like Git, to augment your workflow rather than replace it.


For Data Analysts: From Insight to Implementation Plan

The AI Workbench helps you move from a business question to a validated, production-ready asset.

Start by stating your goal in plain language and get access to relevant data assets or samples to start the analysis in a ready-made notebook environment.

When you identify a key finding, the underlying logic is captured in a machine-readable format, and from there, the system helps generate a complete implementation plan.

This creates a direct path from insight to production code, reducing ambiguity and manual handoffs.

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1/ Start Analysis with AI

Use natural language to get intelligent dataset recommendations and a live specification document.

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2/ Integrated Notebook Environment

Explore data in a guided notebook and capture key findings with one click, translating analytical steps into machine-readable logic.

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3/ From Analysis to Engineering

 In the IDE, review an AI-generated implementation plan with proposed models and tests, then use a single command to generate the production-ready assets.

For Data Engineers: Shift from Reactive Fixes to Proactive Operations

The AI Workbench gives you the tools to manage pipelines more efficiently.

It begins with a unified command center that automatically filters alerts to focus your attention on critical failures. For a given failure, the AI proposes a solution and provides a clear, step-by-step explanation of its logic, turning a black box into a transparent process.

You can then test the proposed fix in a secure, isolated sandbox to prove it works without creating new problems.

Once validated, the system creates a pull request in your existing Git workflow, allowing you to review and merge the change using your familiar processes.

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1/ AI-Powered Pipeline Monitoring

A central command center that surfaces critical failures and provides an AI-generated solution proposal.

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2/ Triage Issues with AI

A transparent, step-by-step view of the AI's investigation, with automated validation in a secure sandbox.

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3/ Automate Fixes with Git

A pull request is automatically generated, letting you review and merge the validated fix within your existing workflow.

 

 

See it in action

Schedule discovery call -->

Choose a date and time that works best for you and book an intro call with us.

Learn more about:

  • the benefits of an agentic data workbench
  • best practices in using AI for data exploration and data monitoring 
  • how the Agentic Workbench can help your organisation
 

 

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Your direct path from data insight to production pipelines

Discover our new AI-assisted workbench, designed to help data analysts and engineers build and operate data pipelines with less friction.

Register for live webinar