Coherence AI-Augmented Testing and Deployment Platform

What is Coherence?

Coherence is a platform designed to enhance AI development workflows, particularly focusing on testing and human supervision. It allows businesses to implement real-time guardrails and automated rules to catch potentially harmful AI responses before they reach customers, thereby minimizing risk and improving accuracy. The platform facilitates the creation of comprehensive synthetic test datasets using advanced techniques like Model Ensembles and Mixture of Agents, enabling developers to test and iterate on AI prompts efficiently.

Beyond its AI testing capabilities, Coherence offers robust tools for cloud infrastructure management and application deployment. It features automated CI/CD pipelines, Infrastructure as Code (IaC) generation, and support for various architectures including containers and serverless. Users can manage environments, secrets, and access controls through an intuitive self-service UI or CLI. Coherence aims to simplify cloud operations, enforce security best practices, and help teams migrate from platforms like Heroku, Render, and Vercel, ultimately reducing developer bottlenecks and accelerating product development.

Features

AI Response Guardrails: Implement automated rules and real-time supervision for production AI outputs.
Synthetic Test Case Generation: Create detailed, realistic test datasets for AI evaluation using advanced techniques.
Prompt Testing & Iteration: Quickly test, evaluate, and refine AI prompts using generated test cases.
Automated CI/CD Pipelines: Provides ready-to-use cloud-native build pipelines or integrates with existing tools.
Automated IaC Generation: Detects infrastructure changes and generates corresponding Infrastructure as Code.
Self-Serve Infrastructure Portal: Manage environments, services, secrets, and RBAC via UI or CLI.
Preview Environments Management: Set up and manage testing environments before deploying to production.
Cloud Deployment Automation: Streamline deployment processes across various cloud accounts.

Use Cases

Evaluating and refining AI model prompts for better performance.
Testing AI applications to ensure response accuracy and safety.
Generating synthetic datasets for comprehensive AI model testing.
Automating cloud application deployment and CI/CD workflows.
Managing cloud infrastructure using automatically generated IaC.
Providing self-service infrastructure access to development teams.
Streamlining QA processes for AI and software development.
Migrating applications from PaaS solutions like Heroku, Render, or Vercel to cloud providers.

FAQs

Can't I generate test cases myself with ChatGPT?

According to Coherence, users may have already tried this and found the results unsatisfactory ('junk'). Coherence aims to provide higher quality through advanced techniques.
Can the synthetic test case generation be trusted?

Coherence suggests users try the platform to evaluate the trustworthiness ('You'll have to see for yourself').