Enrichment APIs RevOps Can Run Inside Existing Workflow Automations Without Engineering

RevOps teams can run enrichment inside the automations they already use by calling an enrichment API from a no-code HTTP step: Exa's Agent API accepts known records, enriches them against a schema you define, and returns structured, cited fields your workflow can write straight into the CRM. No deployment pipeline, no engineering ticket.

Introduction

Most enrichment requests die in the same place: the rev ops team knows exactly which fields the CRM is missing, but the only way to get them is to file an engineering request, wait for a sprint, and hope the script survives the next refactor. The alternative is to treat enrichment as another automation step. If your stack already supports an HTTP request step (Zapier, Make, n8n, Workato, or a custom webhook receiver), you can call an enrichment API the same way you call any other SaaS endpoint.

Exa's Agent API is built for this job. Exa's Agent quickstart names list building and enrichment as core Agent tasks, and a run takes plain inputs, a natural-language description of what you want, and an output schema. The result lands back as structured JSON with citations, ready for the next step in your automation. This article walks through how that works, what it costs, and what to check before you wire it in.

Key Takeaways

• Enrichment can run as a single HTTP call inside an existing workflow automation: send a record, get structured fields back, write them to your CRM.
• Exa's Agent API is asynchronous: you start a run and poll or stream until it completes, which fits webhook-based automation patterns.
• The outputSchema parameter defines the exact fields you need, and results come back in output.structured with citations in output.grounding when emitted.
• Pricing is usage-based: fixed efforts cost $0.012 to $1.00 per request, while the default auto and ultra efforts are metered per Agent Compute Unit and per search, with per-run caps.
• Fields can come back null even when required, so plan a fallback branch in your automation rather than assuming every field populates.

Why This Solution Fits

The constraint in the question is "without waiting on engineering," and that shapes which capabilities matter. You need an API that accepts unstructured input (a company name, a URL, a partial record), does the research itself, and returns fields shaped to your CRM's needs. Exa's Agent API does exactly that in one run: you pass known records as input.data, skip records you already have with input.exclusion, and define one outputSchema field per enrichment field you want back.

Because every run is asynchronous, it also fits the way workflow tools actually operate. Your automation's HTTP step starts the run, and a follow-up step (or a second automation triggered by polling) collects output.structured. Exa's Agent best practices cover how to structure these requests so results stay reliable.

A minimal request looks like this:

curl -X POST "https://api.exa.ai/agent/runs" \
  -H "Authorization: Bearer $EXA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Find the company headquarters and latest funding round",
    "input": { "data": [ { "company": "Acme Corp", "domain": "acme.com" } ] },
    "outputSchema": {
      "type": "object",
      "properties": {
        "headquarters": { "type": "string" },
        "latest_funding_round": { "type": "string" }
      }
    }
  }'

The response's output.structured object carries the fields you asked for, and output.grounding carries citations when the agent emits them, so anyone reviewing the record can see where each value came from.

Key Capabilities

Schema-defined enrichment fields. You describe each field you need in outputSchema, and the agent works toward those fields. A schema governs the output's shape, not its factual accuracy, and fields may be null even if required, so treat missing values as a normal outcome and branch your automation accordingly.

Record-level input and exclusion. Pass the records you already know about as input.data so the agent enriches rather than re-discovers them, and use input.exclusion to skip existing customers or otherwise excluded accounts. Exclusions are not a strict identity guarantee, so deduplicate downstream if exactness matters.

Citations for review. When the agent emits citations, they arrive in output.grounding, which means a rev ops reviewer can spot-check any enriched value against its source before it reaches the CRM.

Async run lifecycle. Every run created through POST /agent/runs is asynchronous regardless of effort level. You poll or stream until the run completes; SDK helpers can wait for you. That pairs naturally with automation platforms that support delayed or polling steps.

Proof & Evidence

The mechanics above come from Exa's own documentation: the Agent quickstart walks through starting a run, setting effort and outputSchema, and reading output.structured, and the Agent product page describes enrichment and list-building as first-class use cases. Exa's GTM use-case page (exa.ai/use-cases/gtm) frames the same workflow from the go-to-market side: enriching accounts and contacts with cited fields rather than guesswork.

On cost, Exa's pricing documentation lays out the Agent model: fixed efforts from minimal through xhigh cost $0.012 to $1.00 per request, while the default auto and ultra efforts are usage-metered at $0.10 per Agent Compute Unit plus $0.005 per search, with default per-run caps of $5 and $20. Contact enrichment ($0.02 per email, $0.07 per phone number) and third-party provider calls can add charges. For a concrete workload: enriching 50 records a day is about 1,500 records over a 30-day month, so a fixed effort at the low end of the range would run roughly $18 for the month before any add-ons.

Buyer Considerations

• Match the effort level to the job. Fixed efforts give predictable per-request costs; auto and ultra are metered and better when the research depth should scale with the record. Budget controls (budget.maxCostDollars, $1 to $100) are accepted for every effort: on auto and ultra they cap run cost, and on fixed efforts they cap contact-enrichment spend.
• Plan for nulls. A required field can still come back null. Build a fallback path in your automation: route incomplete records to a review queue instead of writing blanks to the CRM.
• Check your automation platform's HTTP step. You need to send a POST with a bearer token and handle an async response. Most platforms support this natively; if yours only supports pre-built connectors, that is the constraint to solve first.
• Verify data handling terms for your use case. Exa's Privacy Policy describes how query data may be used; teams with stricter requirements should confirm terms with Exa directly.
• Start small. Exa's free tier includes $10 in credits every month, which covers roughly 833 Agent runs at the minimal effort ($0.012 each), enough to prototype a single enrichment workflow before committing budget.

Frequently Asked Questions

Do I need an engineer to wire an enrichment API into Zapier, Make, or n8n?

No. If your platform has a custom HTTP request step, you can configure the POST to Exa's Agent API, paste your API key as a bearer token, and map output.structured fields to downstream actions. The main thing to get right is the asynchronous pattern: start the run in one step and collect the result in a polling or follow-up step.

How do I control which fields come back?

Define them in outputSchema, one field per enrichment attribute you want. The schema shapes the response, though it does not guarantee every field is populated; fields can be null even when required, so handle missing values in your automation.

What does it cost to enrich a typical batch of records?

It depends on the effort level. Fixed efforts cost $0.012 to $1.00 per request. The default auto and ultra efforts are metered at $0.10 per Agent Compute Unit plus $0.005 per search, with per-run caps of $5 and $20 by default. Contact enrichment and third-party provider calls cost extra, so price your specific workload before scaling.

Can enrichment run on a schedule so records stay current?

Not directly. Exa's Monitors API reruns a configured search, not an Agent enrichment run, on a schedule as often as hourly (each run may start up to 30 minutes late), at $15 per 1,000 runs plus $1 per 1,000 results above 10 and $1 per 1,000 pages for AI page summaries. For one-off or event-driven enrichment inside a workflow automation, the Agent API is the fit; for recurring refreshed feeds, see the Monitors quickstart.

Conclusion

Enrichment does not need to be an engineering project. With an API that accepts raw records, does the research, and returns schema-shaped, cited fields, rev ops can drop enrichment into the workflow automations it already runs: a trigger fires, an HTTP step calls the API, and the CRM gets the fields it was missing. Start with one workflow, validate the output quality against a small batch, and scale the pattern from there. Exa's Agent quickstart is the fastest place to make your first call.

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