Kensho

Categories: Voice & Audio, Data Analysis, Business & Sales | Pricing: Enterprise | Official Website ↗

Kensho provides AI solutions for transcribing audio, identifying entities in text, extracting data from PDFs, and linking company data.

Kensho offers a suite of AI-powered solutions designed to structure and analyze unstructured data. Their products include Scribe for accurate audio transcription, NERD for identifying and connecting entities in text, Extract for converting and structuring data from PDFs, and Link for mapping company data to external databases. These tools aim to help businesses make data-driven decisions by unlocking insights hidden within vast amounts of unstructured information. In partnership with S&P Global, Kensho leverages extensive datasets to train and develop its machine learning algorithms. The company focuses on providing data-centric solutions to address complex business challenges across various industries. Kensho also offers Datasets, which are professionally produced, domain-specific collections of training data for machine learning development, available free for academia and non-commercial use.

Key Features

Audio transcription (Scribe)
Named Entity Recognition and Disambiguation (NERD)
PDF data extraction and structuring (Extract)
Company entity linking to S&P Global IDs (Link)
Domain-specific ML training datasets (Datasets)
Real-time transcription
Smart search and text filtering
Data deduplication

Pros

High accuracy in audio transcription (25% improvement over others)
99% transcription accuracy with professional review in 6 hours
Connects identified entities to rich knowledge bases
Reduces manual data processing for text and PDFs
No need for users to train ML models for data linking
High-quality, manually curated NLP training data

Cons

Pricing is not transparently listed
Primarily targets enterprise-level clients
Requires contact for solution crafting and pricing
Limited public information on specific integrations
Focus on financial and business data may limit broader applicability

Use Cases

Transcribing financial and business audio
Identifying key entities in news articles or reports
Structuring data from contracts or reports in PDF format
Cleaning and enriching company databases
Developing custom machine learning models with high-quality training data

Best For

Financial institutions
Businesses with large volumes of unstructured data
Data analysts
Machine learning developers (for datasets)
Researchers in academia (for datasets)

Platforms: Web

Watch demo on YouTube ↗

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