AI automation workflow system
End-to-end automation fabric connecting forms, APIs, spreadsheets, CRM endpoints, email, and AI models to strip out repetitive manual coordination.
Results at a glance
Fewer copy/paste hops between CRMs, sheets, and comms tools
Explicit webhook contracts instead of one-off cron scripts
Guardrailed AI steps embedded inside auditable flows
Challenge
Operations teams were chaining spreadsheets, lightweight scripts, and inbox reminders to move leads and tickets forward—fragile when APIs changed and impossible to observe when something silently stopped.
What Habrig built
- Operator-facing triggers and approvals surfaced through existing tools (forms, chat bots, CRM views) rather than a bespoke portal unless warranted
- n8n and Make.com graphs with retries, error branches, and correlation IDs across steps
- REST + webhook integrations into CRMs, SaaS products, and internal services
- OpenAI-assisted classification or drafting steps confined to reviewed templates
- Secrets handling outside plaintext sheets; environment separation for sandbox versus production graphs
- Runbooks for replaying failed payloads without duplicating side effects
Outcomes
- Automation graphs that teammates can read and adjust without reverse-engineering bespoke code
- Measurable reduction in manual ticket updates and routing latency
- Safer iteration because AI touches sit inside monitored workflows—not shadow IT scripts
Technology
frontend
Thin UI layers where human approvals matter; otherwise native SaaS surfaces
backend
Orchestration in n8n / Make with OpenAI and REST integrations
database
Google Sheets or lightweight stores as systems of collaboration where appropriate; CRM remains source of truth
infrastructure
Hosted automation runners with encrypted credentials and scoped API keys
monitoring
Execution logs, failure alerts, and periodic reconciliation jobs
cicd
Export/version workflow definitions and promote changes through staging tenants
Execution detail
Product & frontend
- Operator-facing triggers and approvals surfaced through existing tools (forms, chat bots, CRM views) rather than a bespoke portal unless warranted
Backend & data
- n8n and Make.com graphs with retries, error branches, and correlation IDs across steps
- REST + webhook integrations into CRMs, SaaS products, and internal services
- OpenAI-assisted classification or drafting steps confined to reviewed templates
Platform & delivery
- Secrets handling outside plaintext sheets; environment separation for sandbox versus production graphs
- Runbooks for replaying failed payloads without duplicating side effects
Plan your next release
Tell us what shipped, what is at risk, and what success looks like. We will respond with a practical path.
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