Adaline

About Adaline

Adaline is a collaborative platform that enables product and engineering teams to iterate, evaluate, and monitor prompts for large language models (LLMs) using intelligent evaluations and version control. By automating prompt testing and providing real-time performance analytics, Adaline helps teams reduce costs and improve the reliability of their AI applications.

```xml <problem> Developing and maintaining large language model (LLM) applications requires rigorous prompt engineering, testing, and monitoring to ensure reliability and minimize costs. Teams often lack a centralized platform to collaboratively iterate on prompts, evaluate performance across diverse datasets, and track changes over time. This can lead to inefficiencies, increased risk of errors, and difficulty in optimizing AI application performance. </problem> <solution> Adaline provides a collaborative platform designed to streamline the entire LLM application lifecycle, from prompt engineering to production monitoring. The platform offers a centralized workspace for teams to iterate on prompts, evaluate performance using intelligent evaluations, and manage versions effectively. Adaline automates prompt testing across thousands of data rows, providing real-time performance analytics and continuous testing capabilities. By offering tools for prompt management, performance tracking, and issue debugging, Adaline enables teams to optimize their AI applications, reduce costs, and ensure consistent performance in real-world scenarios. The platform supports major LLM providers and models, allowing users to switch between them and fine-tune parameters for optimal results. </solution> <features> - Collaborative playground for prompt engineering with support for chat threads and multiple LLM providers (OpenAI, Anthropic, Google Gemini) - Variable support for incorporating context from Retrieval-Augmented Generation (RAG) pipelines or user questions - Automated version history for prompts, enabling easy restoration and change tracking - Intelligent evaluations, including context recall and LLM-powered rubrics, to assess model output quality - Heuristic-based evaluations for response latency and content filtering - Debugging tools for identifying and addressing issues, with filtering capabilities for failing tests - Production logging to evaluate completions against established criteria - Analytics dashboard with insights into inference counts, evaluation scores, cost metrics, and token usage - Datasets module to build datasets from real data using Logs, upload CSVs, or collaboratively build and edit within the Adaline workspace - Multi-environment deployments to manage the entire lifecycle from development to production with environment-specific configurations </features> <target_audience> Adaline is designed for product and engineering teams building AI-powered applications, including those in enterprises and fast-scaling startups. </target_audience> ```

What does Adaline do?

Adaline is a collaborative platform that enables product and engineering teams to iterate, evaluate, and monitor prompts for large language models (LLMs) using intelligent evaluations and version control. By automating prompt testing and providing real-time performance analytics, Adaline helps teams reduce costs and improve the reliability of their AI applications.

Where is Adaline located?

Adaline is based in Seattle, United States.

When was Adaline founded?

Adaline was founded in 2024.

Who founded Adaline?

Adaline was founded by Akshay G..

  • Akshay G. - Co-Founder/CTO
Location
Seattle, United States
Founded
2024
Employees
10 employees
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Adaline

Score: 65/100
AI-Generated Company Overview (experimental) – could contain errors

Executive Summary

Adaline is a collaborative platform that enables product and engineering teams to iterate, evaluate, and monitor prompts for large language models (LLMs) using intelligent evaluations and version control. By automating prompt testing and providing real-time performance analytics, Adaline helps teams reduce costs and improve the reliability of their AI applications.

adaline.ai50+
Founded 2024Seattle, United States

Funding

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Team (10+)

Akshay G.

Co-Founder/CTO

Company Description

Problem

Developing and maintaining large language model (LLM) applications requires rigorous prompt engineering, testing, and monitoring to ensure reliability and minimize costs. Teams often lack a centralized platform to collaboratively iterate on prompts, evaluate performance across diverse datasets, and track changes over time. This can lead to inefficiencies, increased risk of errors, and difficulty in optimizing AI application performance.

Solution

Adaline provides a collaborative platform designed to streamline the entire LLM application lifecycle, from prompt engineering to production monitoring. The platform offers a centralized workspace for teams to iterate on prompts, evaluate performance using intelligent evaluations, and manage versions effectively. Adaline automates prompt testing across thousands of data rows, providing real-time performance analytics and continuous testing capabilities. By offering tools for prompt management, performance tracking, and issue debugging, Adaline enables teams to optimize their AI applications, reduce costs, and ensure consistent performance in real-world scenarios. The platform supports major LLM providers and models, allowing users to switch between them and fine-tune parameters for optimal results.

Features

Collaborative playground for prompt engineering with support for chat threads and multiple LLM providers (OpenAI, Anthropic, Google Gemini)

Variable support for incorporating context from Retrieval-Augmented Generation (RAG) pipelines or user questions

Automated version history for prompts, enabling easy restoration and change tracking

Intelligent evaluations, including context recall and LLM-powered rubrics, to assess model output quality

Heuristic-based evaluations for response latency and content filtering

Debugging tools for identifying and addressing issues, with filtering capabilities for failing tests

Production logging to evaluate completions against established criteria

Analytics dashboard with insights into inference counts, evaluation scores, cost metrics, and token usage

Datasets module to build datasets from real data using Logs, upload CSVs, or collaboratively build and edit within the Adaline workspace

Multi-environment deployments to manage the entire lifecycle from development to production with environment-specific configurations

Target Audience

Adaline is designed for product and engineering teams building AI-powered applications, including those in enterprises and fast-scaling startups.