Build n8n Automation Portfolio Case Studies

Here are your n8n projects, based on what you’ve told me. I only list what you’ve actually described, so add real numbers (leads, time saved) wherever you can. Numbers make a portfolio far more convincing.

Upload these first (strongest for the jobs we discussed)

1. Instant AI callback and lead update pipeline (ITM)

A lead requests a callback, and an AI voice agent (OmniDimension / Bolna AI) calls them instantly and answers their questions.
When the call ends, an n8n webhook sends the call to an LLM, which marks the lead interested or not interested.
An API call updates the lead stage in Customer.io, which triggers the next action.
Runs on about 1,000 to 2,000 leads per day.
Tools: n8n, Customer.io, OmniDimension, Bolna AI, LLM.

2. ICICI SRM AI calling agent pipeline

n8n reads data from Google Sheets, generates each agent’s configuration with Gemini (structured output parser), and creates the agent through the OmniDimension REST API.
Agent settings: ElevenLabs voice, Deepgram transcriber, GPT-4o-mini, webhook callback, human transfer number, and Hindi persona rules (correct feminine verb forms).
Afterwards you analysed call transcripts and sorted leads into hot, eligible and callback-needed groups.
Contact enrichment through the Lusha API.

3. Lead data pipeline into Customer.io (BBA leads)

An n8n webhook receives lead data, normalizes it, and forwards it to Customer.io. You also built daily lead tracking by querying Customer.io directly.

4. “Shruti” voice agent for MCA lead follow-up

Designed on OmniDimension for follow-up calls to MCA programme leads.
Strong supporting projects

5. Nexi, the AI course generator (versions 1.0 to 4.0)

Built in n8n with OpenAI, ElevenLabs, Ideogram and Kling. Show how it improved across four versions, since that shows you iterate.

6. LMS content generation system

n8n orchestrates the Claude API to produce structured JSON for MongoDB-backed course sessions (track, module, topic, with text, section and media blocks). Optional HeyGen and ElevenLabs for media.

7. Academic Feedback Dashboard

Weekly WhatsApp feedback collection from students through Interakt, orchestrated by n8n, stored in a database with a dashboard on top.

8. WhatsApp AI chatbots for ITM

Deployed across several business units with CRM integration, using Meta WhatsApp Business API.

9. Bulk email workflow

n8n sends email through SMTP with Google Sheets as the data source, with batching.
Not n8n, but worth including as full-stack proof
Placement Radar: Next.js, MongoDB, job scraping with Apify, AI relevance filtering, lead tracking, round-robin assignment, WhatsApp and email communication.
Admissions analytics schema and omnichannel dashboard: lead source tracking, funnel timing, payment tracking, with Looker Studio and Power BI dashboards.
Which to upload for which job
Job Upload
Voice AI right-hand (solo founder) 1, 2, 4, then 3
Lead Recovery Engine (US real estate) 1, 3, 8
AI business automation (healthcare, AU/NZ) 1, 7, 9, plus the analytics dashboard
Before you upload
Confidentiality: ICICI is a client programme, and the others involve students’ data. Describe them as “a banking-sector training programme” or “an education company”, remove names, phone numbers and screenshots with real data, and use dummy data for demos. Check you’re allowed to share workflow files at all, because exported n8n workflows can contain credentials. Remove all API keys and webhook URLs before exporting.
For each project, add: the problem, what you built, the result (even a rough number), and the tools. Four short lines are enough.
I haven’t seen the workflows themselves, so I can’t describe node-level details. If you paste a workflow’s JSON with credentials removed, or describe how one works, I can write a precise case study for it.