Brimit helpt organisaties het potentieel van data en AI te benutten door oplossingen te leveren die operaties verbeteren, kosten verlagen en resultaten verbeteren—brancheoverschrijdend en over alle bedrijfsfuncties heen.
WHAT WE DO
Structuring the lifecycle from discovery, data preparation, model or prompt development, experiment tracking, evaluation, deployment, monitoring, and continuous improvement. For ML: dataset versioning, training pipelines, model registry, CI/CD, endpoint deployment, and retraining triggers. For GenAI: prompt versioning, retrieval tests, golden question sets, safety evaluation, and feedback loops.
Production monitoring covering quality, latency, cost, drift, hallucination risk, retrieval issues, user feedback, incidents, token usage, and usage analytics. Signals help teams decide when to retrain, update prompts, fix data, or roll back a release.
Working with a modern AI delivery toolchain rather than a single fixed platform—cloud-native services, Azure services including Microsoft Foundry and Azure Machine Learning Studio, open-source tools including MLflow, container platforms, workflow orchestration, feature stores, model registries, and evaluation tooling selected for the client's environment.
Implementing CI/CD with Azure DevOps, GitHub Actions, or the client's existing delivery platform—environment promotion, automated tests, evaluation gates, approvals, secrets management, rollback, and release controls. For LLM systems: prompt versioning, retrieval tests, source-quality checks, and controlled rollout to user groups.
Defining access, audit trails, approvals, responsible AI practices, vendor and model selection criteria, security review, documentation, and privacy requirements. Clear governance lets teams move faster because the control model is established before production.
Defining roles, documentation, runbooks, training, service levels, ownership, incident paths, and continuous improvement backlog. Support can be full handover, shared, or ongoing managed improvement depending on the client's operating model.
