# Engineering: applied AI for regulatory compliance and governance

> Applied AI engineering from Sireto: automated regulatory compliance, regulation as code, agentic systems, regulatory knowledge engineering, LLM engineering, AI evaluation, AI infrastructure and secure enterprise integration.

Canonical: https://sireto.com/engineering

## Capabilities

- Automated regulatory compliance: compliance checking systems that evaluate policies, controls and evidence against structured regulatory requirements, with the source provision attached to every finding.
- Regulation as code: legislation, standards and internal policies transformed into structured, machine-executable rules with provenance.
- Agentic systems: multi-agent architectures for research, extraction, validation and operational workflows.
- Regulatory knowledge engineering: regulatory ontologies, knowledge graphs, semantic models and domain knowledge representation.
- LLM engineering: structured generation, model routing, evaluation, prompt optimisation and model-independent architectures.
- AI evaluation: datasets, benchmarks and systematic testing for extraction, reasoning and domain-specific AI systems.
- AI infrastructure: APIs, observability, authentication, orchestration and production infrastructure.
- Secure enterprise integration: connecting AI systems with existing identity, data and operational environments without creating opaque black boxes.

## Principles

Explicit over implicit; provenance by default; model-independent; evaluated, not demonstrated; open representations; no new black boxes.

## Typical problems

Automated regulatory compliance, regulation as code, regulatory change management, AI governance infrastructure, knowledge graph engineering, agentic document processing, AI architecture.

Discuss a project: https://sireto.com/contact?topic=engineering