Capabilities

SagitariusAI provides local and sovereign AI capabilities for defined business needs. The work ranges from focused RAG implementations to model adaptation and agentic workflows.

SagitariusAI develops AI systems from source data through daily operation. Our center of gravity is sovereign, local-first AI: systems an organization can run, inspect, and recover under its own authority. We use external services where they offer a clear advantage, but they do not define the architecture.

These are established areas of technical practice, each serving a different business need. A capability may support a focused engagement or form part of a broader system. We combine capabilities only when the work requires it.

Language models, data, and curricula

Most businesses do not need to train a new language model. Prompting and retrieval should come first. Model adaptation becomes useful when those methods cannot produce stable behavior, meet a specialized requirement, or operate within the required limits.

SagitariusAI first determines whether the model itself needs to change. When it does, we fine-tune an existing model, create a LoRA, or train for a defined curriculum. Testing and documentation make the change measurable rather than assumed.

Most organizations start with knowledge they already own: documents, records, and working procedures. When that knowledge changes often or must remain traceable, retrieval-augmented generation is usually more appropriate than model training.

SagitariusAI prepares the source material, retrieval structure, and tests for a dependable RAG system. We use a training curriculum when the model must learn a behavior or reasoning pattern that retrieval alone cannot supply. In both cases, the source and purpose of the data remain documented.

Agentic software

Agentic software is useful when an AI system must do more than answer a question. It may need to use a tool, move work through several stages, or produce an artifact another person can continue.

SagitariusAI builds these workflows with clear task boundaries and durable records. We add memory only where continuity requires it. Human review remains part of the design wherever the system could affect data, commitments, or release decisions.

Sovereign and local AI infrastructure

Local infrastructure matters when information is sensitive, outside dependency is unacceptable, or the organization needs direct control over continuity. It can also make ownership and operating costs easier to understand.

SagitariusAI designs local-first environments around the organization's data and authority. Systems are built to be observable, recoverable, and maintainable. External compute or services are added only when they serve a defined purpose without surrendering unnecessary control.

Evaluation and release evidence

Evaluation is needed before a business can depend on an AI system. A successful demonstration does not show how often the system fails, where its limits are, or how it behaves under routine conditions.

SagitariusAI tests the system against defined tasks and expected behavior. We record failures and known limits. Release evidence is then used to decide whether the system is ready for broader use.

Synthetic media and communication

Technical work also has to be understood. A business may need to explain a system to customers, document it for operators, or present research in a form people can use.

SagitariusAI produces technical documentation, visual material, and narrated media with AI-assisted systems. Public material remains subject to human review and disclosure. Private or commercially sensitive information stays outside the production package.