// SERVICE · AI WORKFLOW AUTOMATION

Stitchyourtools.Savethehoursback.

WHO THIS IS FOR

For operators drowning in manual work (sales ops, customer ops, support leads, finance teams) who keep finding their team copy-pasting between tools.

We connect your CRM, ticketing, email, and ops tools with AI-powered workflows that hold up in production. Zapier, Make, n8n, and custom code where it matters. Owned by you, documented, and instrumented from day one.

Book a scoping call →See how we work

// USE CASES

What we actually build.

PROBLEM

Ticket triage agent

Support team manually routes 400 tickets/day across 6 queues. 22% mis-routed.

SOLUTION

LLM classifier + n8n routing + Slack approval bridge for low-confidence cases.

STACK

n8nClaudeZendesk

TIMELINE

3–4 weeks

PROBLEM

Sales research automation

BDRs spend 90 min/day researching accounts before outreach.

SOLUTION

Background agent that researches firmographics, recent news, and contacts; drafts the email.

STACK

MakeOpenAIApolloHubSpot

TIMELINE

2–3 weeks

PROBLEM

Invoice processing pipeline

AP team manually keys invoices from PDF/email into NetSuite. 5 hours/week of error-prone work.

SOLUTION

OCR → structured extraction → validation rules → human approval queue → posted entry.

STACK

PythonGPT-4NetSuite API

TIMELINE

4–6 weeks

PROBLEM

CRM hygiene agent

Salesforce data quality decays: duplicate accounts, missing fields, stale stages.

SOLUTION

Nightly agent that dedupes, enriches, and flags anomalies in a review queue.

STACK

n8nClaudeSalesforce

TIMELINE

3 weeks

PROBLEM

Onboarding workflow

Customer-facing teams have a 14-step onboarding that lives in someone's head.

SOLUTION

Workflow with AI-drafted check-ins, document collection, and milestone tracking.

STACK

ZapierOpenAINotion

TIMELINE

2 weeks

// SAMPLE DELIVERABLE

What you walk away with.

automation-handoff/ — 14 files · 2.4 MBmain

📁 automation-handoff/

📄 README.md

📄 architecture.md

📁 evals/

groundtruth.jsonl

dashboard.html

regression.yml

📁 src/

classifier.py

router.js

prompts.yaml

📁 deploy/

terraform/

monitoring.json

📄 runbook.md

🎬 walkthrough.loom

# automation-handoff

## Stack: n8n · Make · Zapier · OpenAI

## What's in here

This repo is the complete handoff for the automation build.

Every workflow is owned by you and runs on your credentials.

## Workflows included

- ticket-classifier — LLM triage + Slack bridge

- sales-research — background enrichment agent

- invoice-pipeline — OCR → validation → NetSuite

## Running evals

$ python evals/regression.py --suite groundtruth.jsonl

## Monitoring

All workflows emit to the dashboard. Error queue threshold: 5%.

See runbook.md for incident response steps.

## Loom walkthrough

18-minute recorded handoff at walkthrough.loom

// FAQ

Common questions for this kind of work.

How is this different from us hiring a Zapier consultant?

A typical Zapier consultant builds the workflow and leaves. We build it as a production system (with logging, error queues, fallbacks, and tests) so it survives schema changes and edge cases without an emergency call.

What happens when the AI gets it wrong?

Every workflow is built with a confidence threshold and a human-in-the-loop fallback for low-confidence cases. We instrument the wrong-call rate so you can see it trend over time, and tune the threshold accordingly.

Do we pay for tool licenses?

You pay platform fees (n8n / Make / Zapier / model APIs) directly to the vendors. We never mark them up. We can run your model calls through our keys during the build to avoid procurement delays.