Connecting the Dots: A Deep Dive into Multi-API Data Enrichment

A new user signs up. You get a name and an email. Is that a lead? A future power user? A churn risk? On their own, these two data points tell you almost nothing. The real value lies in understanding the context behind the user: their company, their role, their technical background, their online presence. This is the goal of data enrichment—transforming a simple contact into a rich, actionable profile.

But building this profile is a complex puzzle. The pieces are scattered across dozens of different services: CRM data from Apollo, social profiles from PeopleDataLabs, professional activity from GitHub, and so on. Manually researching each user is impossible at scale, and traditional automation tools often create brittle, hard-to-maintain chains of API calls. One small change or network hiccup can bring the entire process crashing down.

What if you could define this complex data-gathering and analysis process as a single, reliable, and intelligent service? What if you could treat your business logic with the same rigor as your application code?

The Challenge of Stitching APIs Together

Modern data enrichment isn't just about calling one API. It's about orchestrating a sequence of calls, where the output of one step often becomes the input for the next. This introduces significant technical challenges:

• API Juggling: Each service has its own authentication, rate limits, data schemas, and error codes. Managing this complexity for multiple APIs is a significant engineering effort.
• Brittle Logic: Visual, no-code builders can be great for simple "if-this-then-that" tasks. But for conditional logic, parallel processing, and data transformation, they quickly become a tangled web of boxes and arrows that are impossible to test or version control.
• Error Handling & Retries: What happens if one API in your sequence is temporarily unavailable? A naive implementation will fail the entire workflow, losing valuable data. A robust system needs built-in retries, state management, and clear error logging.
• Maintenance Hell: When an API you depend on changes, how do you find and update every workflow that uses it? Without a code-based approach, you're stuck in "click-ops," manually auditing your automations and hoping you didn't miss anything.

A Better Way: Automation as Code with Workflows.do

The solution is to stop treating business processes as fragile scripts and start treating them as first-class code. At Workflows.do, we enable you to build, deploy, and monitor reliable, event-driven, and AI-powered workflows that connect your entire business stack.

Instead of a messy visual diagram, you define your entire process in clear, concise code. Let's look at how you can build a powerful user-enrichment workflow that triggers on every new signup.

import { AI } from 'workflows.do'

export default AI({
  onUserSignup: async ({ ai, api, db, event }) => {
    const { name, email, company } = event

    // Enrich contact details with lookups from external data sources
    const enrichedContact = await api.apollo.search({ name, email, company })
    const socialProfiles = await api.peopleDataLabs.findSocialProfiles({ name, email, company })
    const githubProfile = socialProfiles.github ? await api.github.profile({ name, email, company, profile: socialProfiles.github }) : undefined

    // Using the enriched details, deeply research the company and personal background
    const companyProfile = await ai.researchCompany({ company })
    const personalProfile = await ai.researchPersonalBackground({ name, email, enrichedContact })
    const socialActivity = await ai.researchSocialActivity({ name, email, enrichedContact, socialProfiles })
    const githubActivity = githubProfile ? await ai.summarizeGithubActivity({ name, email, enrichedContact, githubProfile }) : undefined

    // Schedule a highly personalized email sequence to optimize onboarding
    const emailSequence = await ai.personalizeEmailSequence({ name, email, company, personalProfile, socialActivity, companyProfile, githubActivity })
    await api.scheduleEmails({ emailSequence })

    // Summarize everything, save to the database, and post to Slack
    const details = { enrichedContact, socialProfiles, githubProfile, companyProfile, personalProfile, socialActivity, githubActivity, emailSequence }
    const summary = await ai.summarizeContent({ length: '3 sentences', name, email, company, ...details })
    const { url } = await db.users.create({ name, email, company, summary, ...details })
    await api.slack.postMessage({ channel: '#signups', content: { name, email, company, summary, url } })
  },
})

Let's break down what makes this approach so powerful:

1. Event-Driven Trigger: The entire process kicks off with onUserSignup. This could be triggered by a webhook from your auth provider, a direct API call, or an event from another service.
2. Seamless API Integration: Notice how simple the API calls are: api.apollo.search(...), api.peopleDataLabs.findSocialProfiles(...). Workflows.do handles the authentication, retries, and data parsing, letting you focus on the logic. The conditional check for a GitHub profile (socialProfiles.github ? ...) is clean and easy to read.
3. Built-in AI Intelligence: This is where the magic happens. We're not just fetching data; we're using AI agents to understand it. The workflow uses ai.researchCompany and ai.summarizeGithubActivity to turn raw data into valuable insights. It then uses ai.personalizeEmailSequence to craft a truly tailored onboarding experience based on that comprehensive profile.
4. Actionable Outcomes: The workflow doesn't just stop at analysis. It takes action: scheduling emails, saving the complete profile to your database, and posting a summary to Slack for team visibility.

Why "Business-as-Code" is the Future

Defining your data enrichment pipeline as code with Workflows.do provides unparalleled advantages over traditional automation tools.

• Reliability: Our platform is built for durability. It automatically manages state, retries failed steps with exponential backoff, and provides comprehensive error handling. You can be confident that even complex, long-running processes will complete successfully.
• Observability: Every workflow execution is fully observable. You can see the inputs, outputs, and duration of every step, eliminating the "black box" problem of other systems.
• Version Control & Collaboration: Because your workflow is code, you can use Git to track changes, collaborate with colleagues through pull requests, and write tests to ensure your business logic is correct.
• Power & Flexibility: You are not limited by a predefined set of actions. The combination of first-class code, pre-built API connectors, and powerful AI primitives gives you the power to automate any business process, no matter how complex.

Stop fighting with brittle tools. Start building reliable, intelligent business services. Explore Workflows.do and turn your most complex operational processes into simple, observable code.