Why Traincore?
LLMs Transform Traditional Software Development
The primary method of "programming" large language models is through natural language instructions known as prompts. Mastering the array of techniques required to make these models operate effectively, reliably, and with the appropriate expertise is crucial.
The development, management, and evaluation of prompts for LLMs are notably challenging and differ significantly from traditional software development in several ways:
- Subject matter experts are more critical than ever. As LLMs are applied across various domains, the key insights on optimal performance often come not from software engineers but from domain experts.
- AI output is often unpredictable. Minor changes in prompts can lead to unexpected problems.
- AI outputs are subjective. It's difficult to gauge the effectiveness of products, and without thorough evaluations, large enterprises are hesitant to deploy generative AI in production.
- Inefficient workflows for generative AI are costly in terms of poor performance, wasted engineering efforts, and delays in deployment.
Many organizations struggle with fostering the necessary collaboration among product leaders, subject matter experts, and developers. They often resort to a makeshift collection of tools such as OpenAI Playground, custom scripts, and intricate spreadsheets. This approach is slow and prone to errors, leading to extended delays and pervasive uncertainty.
Traincore addresses the most crucial workflows in prompt engineering and evaluation.
We provide an interactive environment where your domain experts, product managers, and engineers can collaborate to refine prompts. This is supported by robust tools for evaluating prompt performance through both user feedback and automated assessments.
Coding best practices are still applicable. All your assets are meticulously versioned and can be integrated with existing systems like git and your CI/CD pipeline. Our TypeScript and Python SDKs seamlessly integrate with your current codebases.
Companies like Duolingo and AmexGBT use Traincore to manage their prompt development and evaluation, enabling them to deliver high-quality AI features with confidence.
“We implemented Traincore at a pivotal time for Twain when we needed to develop and test numerous new prompts for an upcoming feature release. I cannot imagine how we would have managed without Traincore.” – Maddy Ralph, Prompt Engineer at Twain
Who's it for?
Traincore is an enterprise-grade solution for product teams. We are SOC-2 compliant, offer options for self-hosting, and never train on your data.
Product owners and subject matter experts benefit from the Traincore UI, which allows them to guide AI behavior through intuitive prompt editors with integrated monitoring and evaluation.
Developers appreciate that the Traincore SDK/API easily fits into existing code-based LLM orchestration without introducing unnecessary abstractions, while also eliminating bottlenecks in prompt updates and evaluations.
With Traincore, companies are mastering the complexities of AI development and launching innovative applications with assurance. By providing the right tools, Traincore significantly speeds up AI adoption and facilitates the spread of best practices throughout the organization.
“Our teams use Traincore as our development playground to explore various language models, develop our prompts, and assess performance. We are still in the official onboarding process, but Traincore has already become a vital component of our AI R&D process.“ – American Express Global Business Travel
