Context.ai

About Context.ai

Context.ai is a product analytics platform that utilizes natural language processing to categorize user interactions and extract insights from LLM-powered applications. The platform enables businesses to measure user satisfaction and identify areas for improvement by analyzing conversation transcripts and user feedback signals.

<problem> Developers of applications powered by large language models (LLMs) lack comprehensive tools to understand how users interact with their models and to measure model performance effectively. This makes it difficult to identify areas for improvement and ensure user satisfaction. </problem> <solution> Context.ai provides a product analytics platform that helps businesses understand natural language in their LLM-powered products. The platform ingests conversation transcripts via API and SDKs, then uses natural language processing (NLP) to categorize user interactions, group conversations into relevant topics, and identify user intents and behavior patterns. By tracking implicit and explicit user feedback signals, Context.ai enables businesses to measure user satisfaction and identify areas where the LLM application can be improved. The platform delivers insights into how users are engaging with the application and how the product is performing, allowing teams to flag problem areas and improve the offering. </solution> <features> - Ingestion of message transcripts via API, SDKs, and a LangChain plugin - Automated grouping of conversations into relevant categories using an LLM - Identification of user intents and trends in behaviors - Tracking of performance with implicit and explicit user feedback signals - Analysis of conversation transcripts to determine user satisfaction - Topic tracking to identify risky topics and monitor application responses - SOC 2 Type II compliance - Option for self-hosted deployment for customers with strict data residency requirements </features> <target_audience> The primary customers are product teams and developers building LLM-powered applications who need to understand user behavior and measure model performance. </target_audience>

What does Context.ai do?

Context.ai is a product analytics platform that utilizes natural language processing to categorize user interactions and extract insights from LLM-powered applications. The platform enables businesses to measure user satisfaction and identify areas for improvement by analyzing conversation transcripts and user feedback signals.

Where is Context.ai located?

Context.ai is based in London, United Kingdom.

When was Context.ai founded?

Context.ai was founded in 2023.

How much funding has Context.ai raised?

Context.ai has raised 3500000.

Who founded Context.ai?

Context.ai was founded by Henry Scott-Green.

  • Henry Scott-Green - Co-Founder/CEO
Location
London, United Kingdom
Founded
2023
Funding
3500000
Employees
5 employees
Major Investors
Google Ventures, Tomasz Tunguz
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Context.ai

Score: 100/100
AI-Generated Company Overview (experimental) – could contain errors

Executive Summary

Context.ai is a product analytics platform that utilizes natural language processing to categorize user interactions and extract insights from LLM-powered applications. The platform enables businesses to measure user satisfaction and identify areas for improvement by analyzing conversation transcripts and user feedback signals.

context.ai1K+
cb
Crunchbase
Founded 2023London, United Kingdom

Funding

$

Estimated Funding

$3.5M+

Major Investors

Google Ventures, Tomasz Tunguz

Team (5+)

Henry Scott-Green

Co-Founder/CEO

Alec Barber

Founding Software Engineer

Matt Salisbury

Founding Team

Company Description

Problem

Developers of applications powered by large language models (LLMs) lack comprehensive tools to understand how users interact with their models and to measure model performance effectively. This makes it difficult to identify areas for improvement and ensure user satisfaction.

Solution

Context.ai provides a product analytics platform that helps businesses understand natural language in their LLM-powered products. The platform ingests conversation transcripts via API and SDKs, then uses natural language processing (NLP) to categorize user interactions, group conversations into relevant topics, and identify user intents and behavior patterns. By tracking implicit and explicit user feedback signals, Context.ai enables businesses to measure user satisfaction and identify areas where the LLM application can be improved. The platform delivers insights into how users are engaging with the application and how the product is performing, allowing teams to flag problem areas and improve the offering.

Features

Ingestion of message transcripts via API, SDKs, and a LangChain plugin

Automated grouping of conversations into relevant categories using an LLM

Identification of user intents and trends in behaviors

Tracking of performance with implicit and explicit user feedback signals

Analysis of conversation transcripts to determine user satisfaction

Topic tracking to identify risky topics and monitor application responses

SOC 2 Type II compliance

Option for self-hosted deployment for customers with strict data residency requirements

Target Audience

The primary customers are product teams and developers building LLM-powered applications who need to understand user behavior and measure model performance.