ENGINEERING CASE STUDY · AI & AUTOMATION
AI workflow automation
Engineering case study.
LLM APIS · REST APIS · WEBHOOKS · CRM INTEGRATIONS · WORKFLOW AUTOMATION
Connecting AI services and business systems to reduce repetitive work.
- Role
- Integration and backend engineer
- Type
- Operational automation
- Impact
- 70%+ less manual workload
- Source
- Employer and client systems
01 / OVERVIEW
The project
A set of AI-assisted operational workflows connecting LLM services, backend systems, CRMs, and external business tools to simplify recurring work.
02 / ARCHITECTURE
How it fits together
A typical flow from a business trigger to an AI step and a downstream system.
EVENT
Trigger
A webhook or business event that starts a workflow, such as a new CRM record.
Sends to: Workflow engine
A simplified view built from the documented technologies and responsibilities. Internal details that are not documented are intentionally not assumed. The exact automation platform varies by workflow.
03 / CONTRIBUTION
My contribution
- Designed integrations around operational handoffs between business systems.
- Connected services using APIs and webhooks, with attention to validation and reliable data transfer.
- Contributed to workflows that automated recurring operational tasks.
04 / ENGINEERING
Engineering notes
- Kept workflows maintainable and reviewable rather than treating automation as an opaque sequence of actions.
- The broader automation toolkit includes n8n, Make.com, Zapier, and Zoho Flow; the exact platform can vary by workflow.
05 / OUTCOMES
Outcomes and context
- Relevant automation workflows reduced manual workload by 70%+.
TECHNOLOGY
Tools selected for the work.
- LLM APIs. Recurring work such as classifying, summarising and drafting depends on language understanding that fixed rules cannot cover.
- REST APIs and webhooks. They are the common language of CRMs and business tools, so data moves between systems the moment something happens.
- n8n, Make.com, Zapier and Zoho Flow. Visual workflow tools keep automations reviewable and quick to change, with the platform chosen per workflow and the team already using it.