Kensho

Natural-language and speech AI over verified S&P Global financial data

Business & Finance Enterprise Has API
Researched · Published · Reviewed
RECATOOLS Score
6.8 / 10
Founded
2013
HQ
Cambridge, Massachusetts, USA
Users
Launched
Developer
S&P Global (acquired 2018)

Overview

S&P Global's in-house AI engine. Its LLM-ready API lets you query S&P datasets (Capital IQ financials, transcripts, private-company data) in plain English through Claude or ChatGPT, and Kensho Scribe transcribes earnings calls and financial audio.

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Pricing

Pricing shown for reference only. These figures reflect RECATOOLS research as of 13 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.

Free
Free
No public free tier — contact sales

What you can produce with Kensho

  • LLM-ready API over S&P Global datasets
  • Natural-language querying via Claude / ChatGPT
  • In-line source-document links on financials
  • MCP server and S&P Global agent plugin
  • Access to Capital IQ financials, estimates and private-company data
  • Kensho Scribe financial audio transcription
  • Earnings-call and document transcription
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ASEAN Perspective

Kensho in Southeast Asia

ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).

RECATOOLS Verdict

Kensho is best understood as a data-access layer, not a chatbot. The value is that answers are grounded in verified S&P Global datasets, Capital IQ financials, earnings-call transcripts, private-company financials, estimates, with in-line links back to source documents, so an LLM can retrieve numbers you'd normally dig for by hand. The LLM-ready API and its MCP server plug that data into whatever model you already use, which is the right design for agentic finance workflows. Scribe, the speech-to-text side, claims a roughly 30% error reduction over its prior model and is tuned for financial audio. The obvious limitation: it's sold enterprise-only through the S&P Global Marketplace, with no self-serve trial or public pricing, and it presupposes you already license the underlying S&P data. For institutional research desks inside that ecosystem it's compelling; for anyone outside it, there's no easy on-ramp.

Independent AI-assisted assessment by RECATOOLS.

What people say

Independent user reviews of Kensho are thin, in the vein of enterprise data infrastructure sold to institutions rather than a self-serve product, so most available signal comes from S&P Global's own materials, the S&P Global Marketplace listing and industry coverage rather than G2/Capterra-style crowd reviews.

Founded in 2013 and acquired by S&P Global in 2018 (a deal reported around $550M), Kensho has since operated as the parent's AI arm. Its current flagship, the LLM-ready API, is positioned as a bridge between large language models and S&P Global's structured datasets: customers connect a model such as Claude or ChatGPT and query Capital IQ Financials, transactions, earnings-call transcripts and, more recently, S&P Global Private Company Financials and Capital IQ Estimates using natural language. A frequently highlighted feature is in-line source-document links on public financials data, aimed at the auditability that finance teams require, plus an MCP server and S&P Global plugin for agentic setups.

Kensho Scribe, the transcription product, is cited for a roughly 30% reduction in errors versus the previous model, targeting earnings-call and meeting-note documentation where financial terminology trips up general-purpose speech engines.

What's consistently noted, rather than reviewed, is the go-to-market: everything is enterprise-sales-only via the S&P Global Marketplace, with a "Request More Information" flow instead of published pricing or a public trial. That makes it effectively inaccessible to individual developers and small firms, and it assumes an existing S&P Global data relationship.

Because crowd-review coverage is limited, buyers should weigh this as an institutional data-and-retrieval layer whose credibility rests on the quality and licensing of the underlying S&P Global data and on fit with existing workflows, not on a body of public user ratings. Its strongest use cases are inside capital-markets and investment-research teams already operating in the S&P ecosystem.

Summary of public user & expert reviews, compiled by RECATOOLS.

About this listing

Researched on
Published on
Last reviewed

This entry was compiled from publicly available data including Kensho's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Kensho unless explicitly stated.

Data accuracy

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