Kensho Link
A more powerful Kensho Link is now available, designed to make entity matching faster, smarter, and more scalable. It now supports 70 million public and private companies, including those with accented English characters and non-Latin scripts such as Chinese and Arabic.
The new evolution of Kensho Link uses advanced ensemble modeling, powered by machine learning (ML), natural language processing (NLP), and large language models (LLMs), to seamlessly map your messy company data to S&P Global company IDs and global identifiers. This dramatically reduces the time and effort required to connect your records to the S&P Global data universe.
How Kensho Link Works:
- Accurate Mapping: Kensho Link analyzes submitted company names and attributes—such as address, city, state, country, URL, and aliases—against the entire S&P Global company database to identify the best matches.
- Global Coverage: Supports 70 million public and private companies, including those with accented English characters and non-Latin scripts such as Chinese and Arabic.
- Match Scoring: The model returns the top match (or up to the top five), each with a link score (0–100) that quantifies match strength and confidence.
- Comprehensive Data: Results can include not only the matched identifiers and scores, but also foundational company data like legal name, address, URL, and phone number.
- BECRS Insights: BECRS subscribers gain access to entity identifiers and Ultimate Parent details for deeper company-level details.
Kensho Link enables:
- Efficient Integration: Streamlines the mapping of your company universe to S&P Global identifiers, enabling faster onboarding and scalable enrichment.
- Trusted Insights: Transforms siloed, messy datasets into structured, analysis-ready views for confident decision-making.
- Bulk Processing UI: Submit files up to 100 MB (or 1 million records) and receive results within hours.
- Real-Time API: Single submissions through the REST API are typically processed in less than a second.
- Ready Out-of-the-Box: Kensho Link requires only a company name to start, but accuracy improves with additional information.
Kensho Link offers two access methods: A browser-based drag-and-drop CSV uploader supporting up to 500 MB or 1 million rows (subject to quota), and a REST API for submitting up to 100 entities in JSON format. The results typically returned in seconds depending on input size and quality.
Service Provider Information
Input: Entity Information with examples
The table below represents a row in a database. Click the examples to populate the table and then find a match with Kensho Link. You can also type data directly into each cell, to try examples of your own.
| Entity Name* | Aliases | Country | Address |
|---|---|---|---|
Key Information
Use Cases
Kensho Link dramatically reduces the time and effort required to connect records to the S&P Global data universe for many use cases.
- Users that require instant mapping of incoming company names to S&P identifiers quickly enrich their data and gain insights will often use the Kensho Link API–or even integrate the API into their automated workflow.
- For users that regularly manage large volumes of data, Kensho Link can accurately process a million of entities at a time so they can keep their company databases up to date with the most recent S&P data.
- Companies that are trying to augment their CRMs with S&P data use Kensho Link to first map their customer names to S&P identifiers.
- Kensho Link can help companies dedupe their CRM or other company database.
- S&P Global uses Kensho Link to assimilate new data into the S&P universe for various data ingestion jobs.
Benefits
Link began as an internal project, helping S&P Global more quickly integrate new datasets into its universe before it became a commercial product to assist customers with similar data mapping pain points. To date, the solution has linked nearly 500 million entities for internal and external users.
- Comprehensive Entity Matching: Analyzes submitted company names and attributes—such as address, city, state, country, URL, and aliases—against the full S&P Global company database to identify the best matches. Helps unlock the value of your data by improving entity matching accuracy and efficiency.
- AI-Powered Automation: Reduces manual effort by using advanced ensemble modeling powered by machine learning (ML), natural language processing (NLP), and large language models (LLMs).