Lightcast Skills API Alternatives: 6 Options for Skills Extraction

If you need skills extraction in a commercial product and the Lightcast Skills API is out of reach, the main alternatives are HireLayer Skills and Textkernel Skills Intelligence (self-serve, published prices), HrFlow.ai Tagging and RChilli (part of wider HR data platforms), and the free ESCO and O*NET services if a reference taxonomy without text extraction is enough. This guide explains what changed with Lightcast's free access, what to check before you switch, and how each option compares on size, languages, licence and price.

HireLayer sells one of these APIs, so read our section with that in mind. Every fact about the other tools comes from the publisher's own site or documentation, checked between 7 and 11 October 2026, with the links at the end. For the wider picture, including ROME and JANZZ, see our skills taxonomy API comparison.

The short list

Why teams look for a Lightcast alternative

Lightcast (the company formed from Emsi and Burning Glass) publishes one of the best-known skills taxonomies, formerly called Open Skills: more than 33,000 skills grouped into subcategories and categories, with an endpoint that extracts skills from free text. The taxonomy is still free to browse on the Lightcast website. Using the API is a different matter.

According to Lightcast's API access documentation, free access is now reserved for nonprofit organizations and public-good projects, subject to approval, and capped at 50 skill extraction calls a month. Lightcast says that tier is not meant for production workloads. Any for-profit or production use needs a commercial licence, and the price isn't published: you fill in a form and talk to sales.

Honestly, that is a reasonable model for a company whose main business is labour-market data. But it leaves a gap for a startup or a product team that only wants to turn "MS Excel, Pack Office" into stable skill ids, wich is the exact job many developers used the open API for. That is the gap the options below fill.

What to check before you switch

• Extraction or lookup. Some services read free text and return the skills they find. Others only search a taxonomy by name. If you parse CVs or job ads, you need the first kind.
• The languages of your text. A taxonomy with names in 28 languages does not mean the extractor reads 28 languages. Test with the text your users actually write.
• Unknown skills. When a phrase matches nothing, does the API guess the nearest skill or tell you it found nothing? Guesses pollute search and matching quietly.
• Stable ids and a full download. You will store ids, not names, so check that the ids are stable and that you can get the whole taxonomy to build filters and facets.
• A price you can model. Per call, per item or per character changes the bill a lot once you run every CV through it.

The alternatives

HireLayer Skills

HireLayer Skills resolves free text in French or English, from one skill to a whole CV section of up to 5,000 characters, to a taxonomy of 11,061 skills. Each result has a stable id, a type (hard skill, software, certification, soft skill or language), its families and domains, the part of the text it was found in, and, when there is one, a broader skill to widen a search (Excel to Microsoft Office). Text that matches nothing comes back in a seperate unresolved list with likely families, rather than a guess.

One call costs one credit whatever the length of the text, the free plan includes 50 credits a month, and you sign up without talking to anyone. You can download the whole taxonomy with GET /api/v1/skills. Here is the example from the API reference, with names returned in English:

curl -X POST https://hirelayer.co/api/v1/skills/resolve \
  -H "X-API-Key: $HIRELAYER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"text":"React, Node, Cobol, gestion de projet","language":"en"}'

{
  "language": "en",
  "skills": [
    {
      "id": "react",
      "name": "React",
      "type": "software",
      "mention": "React",
      "families": [
        {
          "id": "frontend_development",
          "name": "Frontend development",
          "domain_id": "software_development"
        }
      ],
      "domains": [
        {
          "id": "software_development",
          "name": "Software Development"
        }
      ],
      "broader": null
    },
    {
      "id": "node_js",
      "name": "Node.js",
      "type": "software",
      "mention": "Node",
      "families": [
        {
          "id": "backend_development",
          "name": "Backend development",
          "domain_id": "software_development"
        },
        {
          "id": "programming_languages",
          "name": "Programming languages",
          "domain_id": "software_development"
        }
      ],
      "domains": [
        {
          "id": "software_development",
          "name": "Software Development"
        }
      ],
      "broader": null
    },
    {
      "id": "cobol",
      "name": "COBOL",
      "type": "software",
      "mention": "Cobol",
      "families": [
        {
          "id": "programming_languages",
          "name": "Programming languages",
          "domain_id": "software_development"
        },
        {
          "id": "backend_development",
          "name": "Backend development",
          "domain_id": "software_development"
        }
      ],
      "domains": [
        {
          "id": "software_development",
          "name": "Software Development"
        }
      ],
      "broader": null
    },
    {
      "id": "project_management",
      "name": "Project management",
      "type": "hard",
      "mention": "gestion de projet",
      "families": [
        {
          "id": "project_management",
          "name": "Project management",
          "domain_id": "management_strategy"
        }
      ],
      "domains": [
        {
          "id": "management_strategy",
          "name": "Management, Projects & Strategy"
        }
      ],
      "broader": null
    }
  ],
  "unresolved": [],
  "taxonomy_version": "v1"
}

Best for: products that read CVs and job ads in French and English and want text in, stable ids out, with a published price. It is a smaller taxonomy than Lightcast's, so check the coverage of your niche on a sample first.

Textkernel Skills Intelligence

Textkernel offers skills extraction, normalization, autocomplete and an ontology that links skills and professions: over 12,000 skills with 300,000 synonyms in 25 languages, and 4,500 professions mapped to ISCO and O*NET. Normalizing costs 0.1 credit per input item and extracting from text 0.1 credit plus 0.04 per 1,000 characters, on plans that start at $99 a month. Licensing the full taxonomy structure goes through an account manager.

Best for: multilingual products that need skills and professions in one ontology, the closest match to Lightcast's scope.

HrFlow.ai Tagging

HrFlow.ai's Tagging API returns the top tags for a text with likelihood scores. You can use its own 5,000-label skills tagger or standard taggers for ESCO, O*NET and ROME, and a Taxonomy API lets you maintain your own list. It claims more than 43 languages. Prices are not published.

Best for: teams that want their skills expressed in a public taxonomy such as ESCO or O*NET, and that may use the rest of the HrFlow.ai platform.

RChilli Taxonomy

RChilli exposes skill, job and keyword search over a taxonomy it describes as 3 million skills and 2.4 million job profiles, at 0.3 credit per call, plus an autocomplete add-on at $500 a month. In practice it is a lookup service; skills extraction from documents comes with its resume and job parsers.

Best for: teams already parsing CVs with RChilli.

ESCO

ESCO is the European Commission's classification: 13,939 skills and 3,039 occupations in 28 languages (v1.2.1), free to download and query. Its web service searches and looks up entries but does not extract skills from text. Many teams pair it with an extraction API and keep ESCO ids as the shared reference for reporting.

Best for: a free, multilingual reference taxonomy for European products.

O*NET Web Services

O*NET, run for the US Department of Labor, describes 1,016 occupations with the skills, knowledge and abilities each one requires, under CC BY 4.0. The web services are free after registration. Its skills model is about job requirements rather than a long list of tools, so it replaces Lightcast for occupation data, not for extracting "Kubernetes" from a CV.

Best for: US occupation profiles and career tools.

Moving from Lightcast skill ids

Taxonomies don't share ids, so a switch is a re-resolution, not a find-and-replace. The safe order:

1. Keep the raw text you sent to Lightcast (skills sections, job ads). It is the only input that maps cleanly to any other taxonomy.
2. Run a sample of a few hundred texts through the new API and compare the ouput with your stored Lightcast skills. Look at what is missing, not just at what matches.
3. Store the new ids next to the old ones during the transition, so search, filters and reports keep working while you backfill.
4. Re-resolve the rest in batches, then switch reads to the new ids and drop the old column once nothing depends on it.

When Lightcast is still the right choice

If you need labour-market data, such as job posting volumes, salaries, demand by region or skills trends, none of the APIs above replace it: that is Lightcast's core product, and the comparable vendors are workforce intelligence platforms rather than skills APIs. The same goes if you need its taxonomy specifically, for instance to align with education partners who already use it. Finaly, nonprofits and public-good projects with low volumes can still apply for the free tier.

Frequently asked questions

Sources and further reading

1. Lightcast API access (free and commercial tiers)
2. Lightcast skills taxonomy
3. HireLayer Skills API reference
4. Textkernel Skills Intelligence
5. Textkernel Tx Platform: transaction cost
6. HrFlow.ai Tagging
7. RChilli taxonomies
8. RChilli: plan subscription and cost
9. ESCO: API and web services
10. O*NET Web Services