Kensho AI
Enterprise-ready
Financial intelligence
High accuracy transcription
Advanced NLP
Data structuring
Illuminate insights in the world's unstructured data with AI.
Last updated: Apr 15, 2026
ENTERPRISE
kensho.com
Quick Answer
Kensho AI is an advanced machine learning platform that structures unstructured data for financial institutions. It offers solutions for audio transcription, entity recognition in text, data extraction from PDFs, and company entity mapping. Best for large enterprises and financial organizations needing deep data insights. Free trials are available for individual products, with enterprise pricing for commercial use.
About Kensho AI
Kensho AI provides advanced machine learning solutions for financial institutions and enterprises to transform unstructured data into actionable insights. It offers tools for audio transcription, entity recognition, document data extraction, and company entity mapping. Kensho is the AI and Innovation Hub for S&P Global, leveraging vast datasets for its cutting-edge algorithms.
What Makes It Unique
Kensho's unique value lies in its deep integration with S&P Global's unparalleled breadth and depth of financial data, which it uses to train highly accurate, domain-specific machine learning models for complex financial and business challenges.
Use Cases & Target Users
Use Cases
Best For
Unlocking insights from unstructured financial and business data
Automating data extraction from complex documents for financial analysis
Enhancing financial research with entity recognition and data linking
Improving data quality and deduplication for company databases
Developing domain-specific machine learning models with high-quality training data
Company Size
MEDIUM
ENTERPRISE
Fit Score
Complexity
ADVANCED
Target Team Size
LARGE_TEAM
Target Skill Level
EXPERT
Key Features
Transcribe complex financial and business audio to text (Scribe)
Identify companies, organizations, people, places, and events in text (NERD)
Connect identified entities to rich knowledge bases like Capital IQ or Wikimedia (NERD)
Extract structured data from tables and text in PDF documents (Extract)
Convert PDFs into machine-readable formats for downstream analytics (Extract)
Map messy company data to unique S&P Global Company IDs (Link)
Technical Specifications
API Available
SDK Available
MCP Compatible
Open Source
Team Features
SSO/Enterprise
Webhook Support
Has Demo
Deployment:
CLOUD
Pros
- +25% accuracy improvement over other transcription services for financial audio (Scribe)
- +Ability to identify nearly 100 million entities in text and link to Capital IQ or Wikimedia (NERD)
- +Automates extraction of critical insights from inconsistent PDF documents (Extract)
- +Maps company data to S&P Global IDs for unparalleled data quality and depth (Link)
- +Offers manually curated, high-quality NLP training data for commercial and academic use (Datasets)
- +Backed by S&P Global with access to vast amounts of proprietary data
Limitations
- -Primarily focused on financial and business data, may not be optimal for other domains
- -Enterprise-focused pricing, potentially less accessible for small businesses or individual users
- -Requires integration and technical expertise for full utilization of API-driven solutions
- -Specific pricing details are not publicly available, requiring direct contact for quotes
Decision Intelligence
Best For
Unlocking insights from unstructured financial and business data
Automating data extraction from complex documents for financial analysis
Enhancing financial research with entity recognition and data linking
Improving data quality and deduplication for company databases
Developing domain-specific machine learning models with high-quality training data
Not Ideal For
General-purpose AI tasks outside of financial or business data processing
Users seeking a simple, off-the-shelf SaaS solution without integration needs
Small businesses or startups with limited budgets for enterprise solutions
Creative content generation or image/video editing tasks
Frequently Asked Questions
Your Actions
Dimension Scores
Ease of Use6/10
Output Quality9/10
Value for Money5/10
Customization5/10
Support6/10
Integration1/10
Task Scores
Audit Support
4
Regulatory Compliance
4
Financial Reporting
3
Budget Forecasting
3
Reconciliation
3
Cash Flow Analysis
3
Transaction Processing
2
Expense Management
2
Trust Score
50/100
Limited Data
Based on 5 verified signals
Trust Signals
Verified CompanyS&P Global
Notable CustomersTegus, City University of Hong Kong, Wenzhou-Kean University +5
Funding$123M
Team Size51-200
Data Residency
Switching & Migration
Migration Difficulty
Significant Effort
Data portable as:
API
Email support
Quick Stats
CategoryData Analysis
PlatformsWEB, API
Integrations0+
Views1
LaunchedJan 2013
Setup Timeseconds
AddedMar 2026
Company & Links