Case studies
AI & ML development
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Case studies
AI & ML development

AI Case Studies for Production AI Workflows

AI case studies are useful when they show how a workflow reached production, which constraints shaped the launch, and how live behavior stayed under control.
These examples cover supplier price imports, LLM observability for internal operations, RAG over internal data, AI summaries in ERP workflows, privacy-shaped integration, and guarded AI actions.

Case studies

Each card shows the main risk, what was controlled, and the ownership scope.

Thin slice to production with acceptance criteria

Get Energy / B2B energy platform
Сore risk:
The main risks were branch mapping, period recognition, and price accuracy.
What this case is about:
One bounded workflow reached production through controlled expansion.

LLM observability and incident response

Lazy Ants / Software engineering company
Сore risk:
The value became clearer after launch, the workflow stayed useful.
What this case is about:
Post-launch AI visibility works better when autonomy is bounded and behavior is observable.

RAG in production with cost and latency control

Eurekantine / A smart cloud canteen
Сore risk:
Filtered menu data was sent to the model instead of the full database.
What this case is about:
Retrieval workflows become production-useful when internal data is narrowed before generation.

AI summaries in ERP workflows

Get Energy / B2B energy platform
Сore risk:
The system replaced manual context rebuilding with automated, reusable AI summaries within ERP workflows.
What this case is about:
AI summaries become production-useful when they behave like product artifacts, not disposable output.

Integration under privacy and data rights constraints

Confidential B2B HR platform
Сore risk:
Data privacy and audit constraints forced a narrower scope, excluding sensitive automated actions.
What this case is about:
The workflow moved forward after privacy constraints reshaped the architecture.

Agentic workflow with guardrails

Confidential B2B procurement platform
Сore risk:
Broad automation posed operational risks, so high-impact commercial and compliance decisions required human approval.
What this case is about:
Agentic workflows can reach production when action stays bounded and ownership stays human.
AI case studies | Production AI workflows under real constraints