Prompt Optimization and Experimentation Platform for AI workflows. | Tokyo .

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January 15, 2026 · Tokyo

Variably Prompt Experimentation Platform

See a live demo of a platform for A/B testing prompts, scientific evaluation without LLM-as-judge, ROI measurement, and the underlying architecture.

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Tech stack
  • Next
    Next.js is the full-stack React framework: it delivers high-performance web applications via hybrid rendering and powerful, Rust-based tooling.
    This is the React Framework for production: Next.js enables you to build full-stack web applications with zero configuration and maximum efficiency. It supports a hybrid rendering approach (Server-Side Rendering, Static Site Generation, and Incremental Static Regeneration) for optimal speed and SEO performance. Key features include React Server Components, Server Actions for running server code directly, and the App Router for advanced routing and nested layouts. Developed by Vercel, it leverages Rust-based tools like Turbopack and the Speedy Web Compiler for the fastest possible builds and a superior developer experience.
  • GraphQL
    GraphQL is a data query language for APIs and a server-side runtime (originally developed by Facebook in 2012) that lets clients request *exactly* the data they need, eliminating the over-fetching common with traditional REST endpoints.
    This is a client-driven specification: it shifts data control to the consumer. Unlike REST, GraphQL uses a single endpoint, allowing clients to send a query that specifies the precise data fields required, minimizing payload size and network calls. The API's capabilities are defined by a strongly-typed schema (Schema Definition Language), which acts as a contract between the client and server. This schema enables powerful tooling and introspection. Major platforms like GitHub, Shopify, and Yelp have adopted GraphQL, proving its efficiency for complex, evolving data requirements.
  • Python
    Python: The high-level, general-purpose language built for readability, powering everything from web backends to advanced machine learning models.
    Python is the high-level, general-purpose language prioritizing clear, readable syntax (via significant indentation), ensuring rapid development for any team . Its ecosystem is massive: use it for robust web development with frameworks like Django and Flask, or leverage its power in data science with libraries such as Pandas and NumPy . The Python Package Index (PyPI) provides thousands of community-contributed modules, offering immediate solutions for tasks from network programming to GUI creation . The language is actively maintained by the Python Software Foundation (PSF), with the stable release currently at Python 3.14.0 (as of November 2025) .
  • Go
    Go is Google's open-source, compiled, and statically-typed language built for high-performance, scalable systems (microservices, cloud infrastructure) via simple, efficient concurrency (goroutines).
    Go (often called Golang) is a compiled, open-source language designed at Google by Robert Griesemer, Rob Pike, and Ken Thompson to solve modern software challenges: slow build times and complex dependencies. It is statically-typed and syntactically clean, drawing inspiration from C but adding key features like automatic garbage collection and a powerful, built-in concurrency model (goroutines and channels). This design delivers fast compilation and runtime efficiency, making it the premier choice for building scalable, reliable systems; major projects like Docker and Kubernetes rely on Go for their core infrastructure.
  • PostgreSQL
    PostgreSQL (Postgres): The world's most advanced, open-source object-relational database (ORDBMS), built for reliability and extensibility.
    PostgreSQL is the premier open-source ORDBMS, proven over 35+ years of active development. It adheres strictly to ACID properties (Atomicity, Consistency, Isolation, Durability), ensuring data integrity for mission-critical workloads. Key features include robust SQL compliance, Multi-Version Concurrency Control (MVCC), and superior extensibility (e.g., custom data types, functions in multiple languages). Advanced capabilities like native JSON/JSONB support and the PostGIS extension (geospatial data) make it a powerful, flexible choice for complex enterprise applications.

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