Data pipelines are the circulatory system of the modern enterprise. They move critical information from CRMs, user databases, and third-party APIs into warehouses, analytics tools, and operational systems. But let's be honest: traditional data pipelines are often brittle, high-maintenance, and frankly, not very smart. A minor schema change or a temporary API outage can bring the entire process to a screeching halt, sending alerts to developers and delaying critical business operations.
What if your data pipeline could think for itself? What if it could adapt to errors, make intelligent decisions based on the data it's handling, and execute complex logic without constant human oversight?
This isn't a futuristic dream; it's the reality of agentic AI. Meet Ivy, your autonomous digital worker from .do. Ivy transforms data processing from a rigid set of scripted commands into an intelligent, autonomous business function. It’s time to put your data pipelines on autopilot.
For years, we've relied on ETL (Extract, Tranform, Load) scripts and workflow orchestrators. While powerful, they share common limitations:
These limitations mean your data infrastructure is more reactive than proactive. You're constantly patching holes instead of building a resilient, self-sufficient system.
Ivy is not just another workflow automation tool. It's a digital worker—an autonomous agent you deploy to execute complex tasks as a reliable service. When applied to data processing, Ivy acts like a dedicated data specialist on your team, capable of reasoning, problem-solving, and executing multi-step agentic workflows.
Instead of writing a brittle script, you assign Ivy a high-level goal and give it the tools to succeed.
Imagine you need to process new user signups. With a traditional approach, you'd write a script. With Ivy, you deploy a digital teammate.
import { ivy } from '@do/sdk';
// Create a new instance of your digital worker
const myAgent = ivy.create('ivy-01', {
persona: 'Onboarding Specialist'
});
// Assign a complex, long-running task
const job = await myAgent.assign({
task: 'Process all new user signups from the past 24 hours.',
instructions: [
'Validate email addresses using clearbit.do',
'Create a personalized welcome document using content.do',
'Send a welcome email via courier.do'
]
});
console.log(`Job ${job.id} started. Ivy is on it.`);
In this example, Ivy isn't just mindlessly executing commands. It's managing a business process. If the clearbit.do service is temporarily unavailable, Ivy can be configured to retry, use a backup data source, or flag the record for manual review without stopping the entire batch. This is the difference between simple automation and true autonomy.
Let's make this more concrete. Your goal is to enrich new sales leads, score them, and route them to the appropriate team.
The Old Way: A cron job kicks off a Python script that chains API calls together. If the enrichment API fails for a single lead, the whole process might crash, requiring an engineer to debug and restart it.
The Ivy Way: You deploy an agent with a clear objective.
This is an agentic workflow. Ivy has a goal, a set of tools, and the flexibility to choose the best path to achieve the objective for each piece of data. It handles errors, makes decisions, and executes autonomously in the background. Your developers are freed from pipeline maintenance and can focus on building your core product.
By using Ivy, you fundamentally change your approach to automation. You're no longer just building data pipelines; you're deploying Service-as-Software—a reliable, intelligent service that owns a business function.
It's time to upgrade from fragile scripts to intelligent agents. Let your developers build your business, and let Ivy manage your processes.
Ready to put your data processing on autopilot? Deploy Your First Digital Worker with ivy.do today.
What is ivy.do?
Ivy is an autonomous digital worker on the .do platform. You can configure and deploy Ivy to perform specific business functions and complex workflows, delivered as a reliable software service.
What kinds of tasks can Ivy perform?
Ivy excels at a wide range of tasks, including data processing, lead qualification, customer onboarding, report generation, and support ticket triage. It can integrate with other APIs and services to execute multi-step workflows.
How do I deploy and manage an Ivy agent?
You deploy and manage Ivy through the .do platform's API and SDK. Simply define its role and objectives, grant access to the necessary tools, and assign tasks programmatically. .do handles all the underlying infrastructure.
Is Ivy just another chatbot?
No. While a chatbot reacts to user input in a conversation, Ivy is an autonomous agent that proactively executes complex, long-running business processes in the background. Ivy is a worker, not just a conversationalist.