AI that speaks your domain language

Modern AI assistants such as Claude, Copilot, and ChatGPT are much more useful when they can access your domain knowledge and systems directly. We build custom Model Context Protocol (MCP) servers that expose domain-specific information, validations, workflows, and actions to MCP-capable agents in a structured and secure way.

This is especially valuable for organizations with deep internal knowledge or specialized workflows, where generic AI assistants lack the necessary context and interaction capabilities. We design MCP interfaces around the actual concepts and constraints of your domain to ensure reliable interaction that aligns with your architecture and security requirements.

Bridge the gap between natural language and precise instructions. With DSLs, your prompts gain structure and become part of a spec-driven development process, giving AI models the context they need to reason more reliably and respond consistently.

Semiformal languages combine the flexibility of natural language with the verifiability of formal specifications. Instead of relying on vague, one-off prompts, you express intent through a shared language: precise where correctness matters, flexible where exploration is useful. Domain rules, data models, or constraints are captured explicitly, while natural-language annotations convey intent or design rationale. The same DSL can also be produced as structured output by AI agents, which is easier to review than JSON or similar machine-readable formats and more concise than natural language.

With Langium AI, you can turn your domain-specific language into AIʼs native tongue. We help you connect DSLs with large language models so your tools can reason over structured knowledge, generate valid code, and understand your domain context.

Langium AI grounds LLMs in the actual syntax and semantics of your language instead of letting them guess. It exposes the existing services of your Langium DSL—parsing, validation, and structural information—as building blocks for AI engineering workflows. This makes it possible to evaluate model output reliably and constrain generation to valid language constructs. The result is AI assistance that respects the rules of your language and integrates cleanly with any AI stack you choose.

With Baukasten, our React UI library for domain-specific applications, we help create consistent, maintainable interfaces in VS Code, Eclipse Theia, and web applications. Baukasten provides reusable components, platform-aware styling, and interaction patterns tailored to feature-rich domain tools.

Baukasten is designed for AI-assisted UI development from the start. As coding agents are capable of generating interfaces directly, the challenge shifts from writing UI code to keeping it coherent and maintainable over time. AI models are fast, but not naturally disciplined in following design systems consistently. Baukasten provides an AI-friendly component API and dedicated agent skills that guide models toward reusable abstractions.

We help software teams kickstart new projects with AI-assisted migrations, rapid prototypes, and agent-ready foundations. Domain-specific AI, formal languages, IDE-like user interfaces, and other high-complexity applications require the right abstractions to be understandable, maintainable, and usable.

By combining deep expertise in language engineering, complex toolchains, and modern agentic AI systems, we can move projects from specification to working foundations quickly, without producing throwaway demos or unmaintainable code. The result is a solid technical starting point that internal teams can extend and own confidently.