Find Companies Using Akamai (Technographic API Guide)

Akamai is one of the oldest and largest content delivery networks on the internet, and it skews heavily enterprise. Banks, airlines, streaming platforms, government portals, and large retailers route their traffic through Akamai's edge network because it was built for exactly that kind of scale and reliability. That enterprise bias is what makes “uses Akamai” a genuinely useful technographic signal: unlike a CDN that anyone can switch on with a free tier, an Akamai deployment usually points to a company large enough to have a procurement process, a platform team, and a budget.

This guide explains what Akamai usage tells you about a company, the exact DNS signals that reveal it, and how to turn a raw domain list into an Akamai-confirmed lead list with the DetectZeStack API—starting with a single curl command you can run right now.

Why Find Companies Using Akamai?

Technographic data—what technology a company runs—is frequently a stronger qualifier than firmographics alone. A confirmed Akamai detection is a specific window into a company's infrastructure decisions:

• It signals enterprise scale. Akamai is not a default anyone lands on by accident. Its pricing and sales motion are aimed at large organizations, so a domain routing through Akamai's edge is a strong proxy for a company with real traffic, a real budget, and a real platform team. If your product has an enterprise tier, an Akamai list filters out the hobby projects before you ever open a CRM.
• It maps the buyer. Choosing and configuring an enterprise CDN is a platform, DevOps, or security decision, not a marketing one. Knowing a company runs Akamai tells you which department owns the relationship and which pains are likely to land—origin offload, edge configuration, WAF and bot mitigation, multi-CDN strategy, and cost.
• It establishes maturity. Companies on Akamai have generally been through a performance and reliability procurement cycle. They are past the experimentation stage and serious about global latency and uptime—a useful filter when you want operators rather than side projects.

The same pipeline applies to any detectable technology. We have companion guides for finding companies using Amazon CloudFront and finding companies using Nginx—the filter changes, the workflow stays the same.

How Akamai Detection Works

Akamai is an infrastructure CDN: it sits in front of a site's origin and proxies its traffic, the same role Cloudflare, Fastly, and CloudFront play. Because it operates at the routing layer rather than in the page body, Akamai leaves its clearest and most reliable mark in DNS. When a company points a custom domain at Akamai, that domain does not resolve straight to an origin IP—it CNAMEs into Akamai's edge network, ending in one of a handful of Akamai-owned suffixes.

HTTP Header and DNS Signals DetectZeStack Uses

DetectZeStack identifies Akamai from its DNS CNAME chain. It follows the chain a domain resolves through and matches the terminal hostname against Akamai's known edge suffixes. Here are the suffixes it looks for and what each one represents:

Because Akamai's routing lives in DNS, you can confirm it yourself with a single dig. A real Akamai deployment usually shows a two-hop chain—a vanity host CNAMEs to an edgekey.net mapping name, which in turn resolves into akamaiedge.net:

$ dig www.example.com CNAME +short
www.example.com.edgekey.net.
e1234.x.akamaiedge.net.

Note that Akamai is a DNS-first detection here. Some infrastructure CDNs—CloudFront, for example—also stamp identifying HTTP response headers on every request, which lets them be matched at confidence 100 from the header layer. Akamai's identifying signal in DetectZeStack is the CNAME chain, so it is reported from the DNS layer. That distinction matters for how you read the confidence and source fields, which we cover next. For the broader multi-layer picture across every CDN, see how to detect a website's CDN and hosting provider.

Detect Akamai on a Single Site with the API

You can try detection right now against the public demo endpoint—no API key required. The demo is IP-rate-limited, so use it for spot checks rather than bulk scans:

$ curl -s "https://detectzestack.com/demo?url=example.com" \
  | jq '.technologies[] | select(.name == "Akamai")'
{
  "name": "Akamai",
  "categories": ["CDN"],
  "confidence": 80,
  "description": "",
  "website": "",
  "icon": "",
  "source": "dns",
  "version": "",
  "cpe": ""
}

Akamai is matched off the DNS CNAME chain and categorized under CDN. The entry carries source: "dns" because the evidence came from the CNAME lookup, and confidence: 80—DNS evidence is reliable, but it is deliberately scored below a live HTTP header match, which returns 100. The description, website, icon, version, and cpe fields come back empty for a DNS-sourced detection because that metadata is populated from HTTP fingerprints rather than the CNAME layer. What you can trust from an Akamai entry is the name, the category, the confidence, and the source—which is all you need to build a list.

The /analyze Endpoint Response

When you want the full stack for a domain rather than a filtered slice, call /analyze with your API key. The complete response is shaped like this:

$ curl -s "https://detectzestack.p.rapidapi.com/analyze?url=example.com" \
  -H "X-RapidAPI-Key: YOUR_KEY" \
  -H "X-RapidAPI-Host: detectzestack.p.rapidapi.com"
{
  "url": "https://example.com",
  "domain": "example.com",
  "technologies": [
    {
      "name": "Akamai",
      "categories": ["CDN"],
      "confidence": 80,
      "description": "",
      "website": "",
      "icon": "",
      "source": "dns",
      "version": "",
      "cpe": ""
    },
    {
      "name": "React",
      "categories": ["JavaScript frameworks"],
      "confidence": 100,
      "description": "React is a JavaScript library for building user interfaces.",
      "website": "https://reactjs.org",
      "icon": "React.svg",
      "source": "http",
      "version": "",
      "cpe": ""
    }
  ],
  "categories": {
    "CDN": ["Akamai"],
    "JavaScript frameworks": ["React"]
  },
  "meta": { "status_code": 200, "tech_count": 2, "scan_depth": "full" },
  "cached": false,
  "response_ms": 1642
}

The top-level categories map groups every detection so you can pull all CDNs with .categories["CDN"] without iterating the array. The meta object carries the HTTP status_code, the tech_count, and the scan_depth; response_ms and cached sit at the top level, not inside meta.

One field to watch for list building is meta.scan_depth. A value of "full" means the HTTP fetch succeeded and header detection ran alongside DNS. A value of "partial" means the site blocked or timed out the HTTP request and only the DNS layer completed. Because Akamai is detected from DNS in the first place, a "partial" scan can still confirm it—the CNAME chain resolves whether or not the origin answers. That makes Akamai one of the more resilient signals to scan for: an absent Akamai entry on a "full" scan is a genuine no, while an absent entry on a scan that failed at the DNS step belongs in a retry queue.

Confirm Akamai on One Domain with /check

When you only care about a single yes-or-no question—does this domain use Akamai?—the /check endpoint gives you a compact boolean answer instead of the full technology array. Pass the domain and the technology name you are testing for:

$ curl -s "https://detectzestack.p.rapidapi.com/check?url=example.com&tech=Akamai" \
  -H "X-RapidAPI-Key: YOUR_KEY" \
  -H "X-RapidAPI-Host: detectzestack.p.rapidapi.com"
{
  "domain": "example.com",
  "technology": "Akamai",
  "detected": true,
  "confidence": 80,
  "version": "",
  "categories": ["CDN"],
  "response_ms": 812,
  "cached": false
}

The tech match is case-insensitive, and the response echoes back the canonical technology name in the technology field. When Akamai is not present, detected is false and confidence is 0. This is the endpoint to reach for when you are enriching an existing CRM one record at a time and want a single column—uses_akamai—rather than the whole stack.

Scan a List of Prospects with /analyze/batch

Running dig and /check by hand works for one-off lookups, but it does not scale to thousands of domains. For list building, POST /analyze/batch accepts up to 10 URLs per request and analyzes them concurrently. Each entry in the response carries either a full analysis result or an error for domains that could not be fetched:

$ curl -s -X POST "https://detectzestack.p.rapidapi.com/analyze/batch" \
  -H "X-RapidAPI-Key: YOUR_KEY" \
  -H "X-RapidAPI-Host: detectzestack.p.rapidapi.com" \
  -H "Content-Type: application/json" \
  -d '{"urls": ["example.com", "akamai.com", "delta.com"]}'

The response wraps one result object per URL, each with the same shape as a single /analyze response:

{
  "results": [
    { "url": "example.com", "result": { "...full analysis..." : "" } },
    { "url": "akamai.com",  "result": { "...full analysis..." : "" } },
    { "url": "delta.com",   "result": { "...full analysis..." : "" } }
  ],
  "total_ms": 2210,
  "successful": 3,
  "failed": 0
}

Because each result matches the single-domain shape, the filtering logic is identical whether you scan one domain or a thousand. Here is a complete, copy-pasteable pipeline using nothing but bash, curl, and jq. It reads domains.txt (one domain per line), sends batches of 10 to /analyze/batch, and appends every domain where Akamai is detected to akamai_leads.csv, recording the tech count alongside it:

#!/usr/bin/env bash
# find-akamai.sh — filter a domain list down to Akamai-confirmed leads
KEY="YOUR_KEY"
HOST="detectzestack.p.rapidapi.com"

echo "domain,tech_count" > akamai_leads.csv

# Process domains.txt in batches of 10 (the /analyze/batch maximum)
xargs -n 10 < domains.txt | while read -r batch; do
  urls=$(printf '%s\n' $batch | jq -R . | jq -s '{urls: .}')
  curl -s -X POST "https://$HOST/analyze/batch" \
    -H "X-RapidAPI-Key: $KEY" \
    -H "X-RapidAPI-Host: $HOST" \
    -H "Content-Type: application/json" \
    -d "$urls" |
  jq -r '.results[]
    | select(.result != null)
    | .result as $r
    | select([$r.technologies[].name] | index("Akamai"))
    | [$r.domain, ($r.meta.tech_count | tostring)]
    | @csv' >> akamai_leads.csv
done

wc -l akamai_leads.csv

A 1,000-domain list becomes 100 batch calls. The index("Akamai") guard keeps a domain whenever Akamai appears in its technology list, and select(.result != null) skips domains that failed to resolve (those come back with an error field instead of a result). For a deeper treatment of batch throughput, retries, and a production Python scanner, see how to batch scan 1,000 websites.

Turning Akamai Detection into a Prospect List

An Akamai-confirmed list is rarely the end goal on its own—it is the entry point to a more specific segment. Two enrichment moves make it sharper:

• Cross-reference the rest of the stack. Akamai tells you the CDN; the rest of the technologies array tells you what sits behind it. A site that returns Akamai alongside an enterprise CMS, a Java or .NET signal, or a commercial analytics suite paints a different picture than one running Akamai in front of a lightweight marketing site. Splitting your list on the origin technology turns a broad “uses Akamai” segment into precise sub-segments you can message differently.
• Score by meta.tech_count. The tech count is a rough proxy for how built-out a company's stack is. An Akamai site with a deep technology fingerprint is generally a more mature, more heavily engineered operation—useful for prioritizing which accounts to work first.

Three common ways teams put the finished list to work:

• Sales and prospecting. If you sell CDN tooling, multi-CDN management, edge compute, observability, or a security product that complements or competes with Akamai, an Akamai list is a precise, enterprise-weighted audience. The detection narrows the market to companies whose scale your product actually fits. The same approach drives the Stripe technographic prospecting playbook—swap the technology, keep the method. For wiring the results into your CRM, see tech stack enrichment for sales teams.
• Competitive intelligence. Scanning a market segment for CDN choice tells you how an entire space builds. A cohort heavy on Akamai is making different infrastructure bets—usually more enterprise ones—than one on Cloudflare or Fastly, useful context when you study how a market makes platform decisions.
• Security and attack-surface mapping. Security teams inventory which CDNs and clouds a domain depends on as part of third-party-risk and attack-surface reviews. The CDN category is exactly the layer they need to enumerate, and Akamai frequently pairs with its own WAF and bot-management products worth noting.

Pricing and Rate Limits

Every DetectZeStack plan includes header, DNS, and TLS detection—the Akamai CNAME matching described here is not a premium add-on, it runs on every request at every tier. Plans differ only in monthly request volume:

A /analyze/batch call counts each URL in the batch against your monthly quota, so a 10-URL batch spends 10 requests. The free tier's 100 requests is enough to validate the pipeline on a sample of your prospect list before scaling up; a 10,000-domain scan fits comfortably inside the Ultra plan.

Get Your API Key

The free tier includes 100 requests per month with no credit card—enough to prove the pipeline works on your own prospect list before you commit to a paid plan. Sign-up is instant through RapidAPI:

1. Get a key at rapidapi.com/mlugoapx/api/detectzestack.
2. Spot-check a domain you know: curl -s "https://detectzestack.com/demo?url=yourdomain.com" | jq '.technologies[].name'
3. Run the batch script above against your first 100 domains.

Conclusion

Finding companies using Akamai comes down to reading DNS well. Akamai's edge network gives itself away in the CNAME chain—akamaiedge.net, edgekey.net, edgesuite.net, and the rest—and DetectZeStack matches those suffixes automatically, reporting Akamai under the CDN category at confidence 80 with source: "dns". A single /check call answers the one-domain yes-or-no; /analyze returns the whole stack; and /analyze/batch turns a raw domain list into an Akamai-confirmed lead list. Because the signal lives in DNS, it holds up even when a site strips its response headers—one of the more resilient technographic filters you can build a list around. Swap the jq filter and the same pipeline segments by any other CDN, cloud, or backend technology instead.