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Platform Automation Systems
SELF-HOSTED · PRODUCTION PIPELINES

Your Business RunsOn Manual WorkIt Doesn't Have To.

We build automation systems — not Zapier flows. Real pipelines with error handling, retry logic, failure alerts, and observability. Built on self-hosted n8n, custom webhooks, and API integrations — running in production across six live products every day.

n8nSelf-hosted automation engine
6Products with live pipelines
24/7Pipelines running continuously
0Silent failures tolerated
See Our Live Products →
cipherbitz-core-pipeline — running
Active — 847 executions today
Last run: 2 min ago
true →false
TRIGGER
Webhook
POST /new-lead
847×
CONDITION
Check source
lead.source==='organic'
847×
ACTION
CRM + Slack
POST → API
712×
OUTPUT
Log to Airtable
trigger email
712×
NOTIFY
Slack Alerts
#ops-alerts
712×
ERROR
Retry × 3 → Slack
135×
12:34:02 lead.source=organic → CRM updated12:33:58 lead.source=organic → CRM updated12:33:51 retry 3/3 failed → Slack alert sent12:33:44 lead.source=organic → CRM updated
SIX PIPELINE TYPES

Six Automation Categories.All Production-Ready.

Each pipeline type solves a different class of repetitive work. Together they cover the full operational surface of a digital product — from lead to invoice to alert.

PIPE 01

Lead & CRM Pipelines

WebhookEnrichCRM

Automate the full lead journey — from form submission or webhook trigger to CRM record creation, lead scoring, owner assignment, and Slack notification. No manual copy-pasting between tools.

  • Form submit → tag + assign + notify Slack
  • Lead source tracking → attribution tagging
  • Follow-up sequence trigger on status change
Failure Handling:Retry ×3 → Slack alert → log to DB
→ CipherBitz client intake pipeline
PIPE 02

Content & Publishing Pipelines

ScheduleGeneratePublish

Schedule-triggered pipelines that pull content from a source, optionally enrich with AI (title rewriting, meta generation, category tagging), and publish to WordPress, Ghost, or a custom CMS via REST API.

  • Cron job → fetch data → generate page → publish
  • AI meta description generation on new posts
  • Sitemap ping + search console submission
Failure Handling:Log failed publish → retry next cycle
→ NammaHubballi listings pipeline
PIPE 03

Notification & Alert Systems

MonitorConditionAlert

Event-driven pipelines that monitor product metrics, server health, user actions, or database thresholds — and send structured alerts to Slack, email, or SMS when defined conditions are met. Silent failures end here.

  • Server CPU spike → immediate Slack alert
  • Daily revenue digest → Slack 9 AM summary
  • User signup milestone → team celebration ping
Failure Handling:Dead man's switch — alert if no ping received in defined interval
→ CipherBitz infrastructure monitoring
PIPE 04

Invoice & Billing Automation

TriggerGenerateSend

Trigger-based pipelines that generate invoices, schedule payment reminders, track overdue status, and escalate to human review at defined thresholds. Reduces billing admin to zero for standard invoice cycles.

  • Subscription renew → generate + send invoice
  • Overdue +7 days → reminder email sequence
  • Payment confirmed → update DB + notify ops
Failure Handling:Retry send ×3 → fallback to manual queue with Slack notification
→ FreeBill recurring client pipeline
PIPE 05

Data Sync & ETL Pipelines

ExtractTransformLoad

Scheduled pipelines that extract data from one source (API, spreadsheet, DB table), transform it (clean, map, enrich), and load it into a target system. Keeps multiple systems in sync without manual export-import operations.

  • CRM → analytics DB nightly sync
  • Product catalog → SEO content pipeline
  • User events → reporting dashboard refresh
Failure Handling:Schema validation on transform → reject malformed rows, log + alert
→ FinCalc data pipeline, NammaHubballi
PIPE 06

Onboarding & Lifecycle Sequences

SignupSequenceConvert

Event-triggered email and notification sequences based on user lifecycle events — signup, first action, inactivity, conversion, churn risk. Not bulk email blasts — individual behavioural sequences triggered by what users do.

  • Signup → welcome + D3 + D7 + D14 sequence
  • Inactive 14 days → re-engagement branch
  • First invoice created → upgrade nudge
Failure Handling:Sequence state persisted — resume from last step on restart
→ FreeBill, MNCJob onboarding flows
HOW WE BUILD PIPELINES

Five Phases.Zero Silent Failures.

Every automation we build goes through the same five-phase process — from mapping the happy path to stress-testing the failure paths. A pipeline that has not been tested to failure has not been tested.

"We map the error path before we build the happy path. Most automations fail silently — ours fail loudly, once, with a clear message telling you exactly what broke."

Phase 1 of 5
1

Workflow Mapping

Day 1

Before writing a single node in n8n, we map every step of the workflow on paper — or in a Figma flow diagram. Trigger event, all possible input states, every conditional branch, the happy path, every failure path, retry strategy, and what alert fires when. Only when the map is complete and reviewed does any build begin.

  • Full workflow map (happy path + all error paths)
  • Trigger event specification and payload schema
  • Error handling strategy per failure type
2

Happy Path Build

Day 2–3

Build the main pipeline flow first — the path where every input is valid, every API responds correctly, and every condition passes as expected. Test with real data in a staging environment. Do not move to error handling until the happy path is demonstrably stable.

  • Main pipeline built and tested in staging
  • Real payload test with production-like data
  • Execution logs reviewed — no unexpected behavior
3

Failure Path & Error Handling

Day 3–4

Every API call that can fail has a retry strategy. Every retry strategy has an exhaustion handler. Every exhaustion handler sends a structured alert (Slack + log) with the exact failure reason, the input that caused it, and the last successful execution timestamp. Silence is not an option.

  • Retry logic per API call (attempt count defined)
  • Exhaustion handlers with structured Slack alerts
  • All error states logged to DB with payload
4

Stress Testing & Edge Cases

Day 4–5

Simulate bad input, API timeouts, partial failures, network interruptions, and out-of-order events. We deliberately try to break the pipeline before it goes to production — because it is far better to discover failure modes in testing than at 2 AM on a Sunday.

  • Malformed input test suite documented and passed
  • API timeout simulation tested and handled
  • Concurrent execution test (no race conditions)
5

Monitoring Setup & Handoff

Day 5

Production deployment with monitoring configured from minute one. Execution dashboard in n8n. Slack channel for alerts. Runbook document — what to check when an alert fires, how to restart the pipeline, and what each alert code means. You should never need us to explain what broke.

  • n8n execution dashboard configured
  • Slack alert channel set up and tested
  • Runbook document with alert codes and actions
The Non-Negotiable

Silent Failures Are NotAcceptable. Ever.

A pipeline that runs 99% of the time and fails 1% silently is more dangerous than no pipeline. It builds false confidence while your data drifts, your leads get lost, and your invoices don't send. Our standard: every failure fires an alert. No exceptions.

Transient Failures

Network timeout, API rate limit, brief service outage. These are expected and handled automatically.

Our Response

Exponential backoff retry — attempts 1, 2, 4 minutes. After 3 failures: Slack alert with exact error code and last successful run time.

Data Failures

Malformed input, unexpected payload schema, null values in required fields, type mismatches. These are caught before the pipeline runs.

Our Response

Input schema validated at pipeline entry. Invalid records are rejected immediately, logged with full payload, and flagged to Slack. The pipeline continues for valid records.

Systemic Failures

Downstream service permanently down, DB connection pool exhausted, infrastructure issue, credential rotation. These require human intervention.

Our Response

Pipeline halts immediately. Structured Slack alert with severity level, affected pipeline name, last successful execution, and the exact error message. Runbook reference included in every alert.

How we compare to typical no-code tools

Zapier/Make
Basic n8n
CipherBitz
Silent failuresCommon — task history only
Possible — requires config
✓ Zero — all failures alert Slack
Retry logicLimited — 3 attempts, fixed
Manual config required
✓ Custom strategy per pipeline
ObservabilityTask history — limited detail
Execution log — no alerting
✓ Dashboard + Slack + runbook
Complex branchingPremium plan required
Supported — no structure
✓ Mapped + documented
Self-hosted control✗ Cloud only
✓ Possible
✓ Standard — your data, your server
Running In Production

Three Live Pipelines.Real Numbers. Right Now.

Not demo pipelines. Not concept diagrams. Production automation running every day — with execution counts, uptime, and last-run timestamps that are real.

FreeBill

BUSINESS SAAS

"Recurring invoice + reminder sequence"

0Invoices automated
0Success rate
0Avg execution time
ScheduleGenerateSend

Retry ×3 on SMTP failure → Slack alert

ACTIVE
Last run: 2 min ago

NammaHubballi

LOCAL CITY DIRECTORY

"Listings sync + SEO content pipeline"

0Manual interventions this month
0Published without manual touch
0Manual interventions this month
CronTransformPublish

Schema validation rejects malformed listings

ACTIVE
Last run: 2 min ago

CipherBitz Ops

INFRASTRUCTURE MONITORING

"Server health + daily ops digest"

0Daily digest time
0Alert to human response SLA
0Running without interruption
MonitorEvaluateAlert

Dead man's switch — alerts if no ping in 1h

ACTIVE
Last run: 2 min ago
The Honest Take

When We Tell YouNot To Automate.

Automation for its own sake is vanity. Every pipeline we recommend to not build has a reason — and we will tell you that reason directly, before any quote is written.

Processes you haven't fully understood yet.

If you cannot describe every step, every input, every edge case, and every expected output of a process on paper — you are not ready to automate it. Automating a poorly understood process produces a perfectly reliable machine that reliably produces wrong results.

When To Reconsider:When you can draw the full workflow map, including all edge cases, without ambiguity.

Tasks that will run fewer than 50 times.

Building a pipeline for a one-time data migration, a single campaign send, or a task that runs once a quarter is almost never worth the build time, testing effort, and maintenance burden. A well-written script or manual process costs less and carries less ongoing risk.

When To Reconsider:When the task is recurring, high-volume, or error-prone when done manually.

Business processes that change monthly.

Automation is rigid by design — that is its value. If the process it automates changes every four weeks, every change requires a pipeline update, a test cycle, and a re-deployment. For rapidly evolving processes, a human operator is more flexible and cheaper until the process stabilises.

When To Reconsider:When the process has been stable for at least 3 months and the rules are documented.

Processes requiring human judgment.

Automation executes rules. If the core of a process is a judgment call — evaluating a creative brief, assessing a candidate, making a pricing exception — automation can support the decision but cannot make it. Building a pipeline around a judgment call creates the illusion of a system where none exists.

When To Reconsider:When the judgment call can be reduced to a defined scoring rule or threshold — then it becomes automatable.

When you won't monitor what breaks.

A pipeline with no monitoring is a liability. If the automation runs at 2 AM and you will not check the execution log until next week, you need alerting infrastructure before you need the automation itself. We will not deploy a pipeline without alerts configured. That is not a policy — it is a requirement.

When To Reconsider:When Slack alerts are configured and someone is responsible for responding within the SLA.
How To Start

Three Ways to StartAutomating Your Business.

MOST POPULAR

Single Pipeline Build

1 week

One automation problem, solved completely. Workflow mapping, build, failure handling, monitoring setup, Slack alerts, and a runbook document. Done in one week. Runs reliably from day one.

  • Full workflow map before any build begins
  • Happy path + all error paths tested
  • Slack alerting configured before handoff
  • Runbook document included
Build My Pipeline →
START HERE

Automation Audit

3 days

Already running pipelines but not sure which ones are failing silently? A 3-day audit of your existing workflows — identifying silent failures, missing error handling, and the three highest-value automation opportunities in your business.

  • Full review of existing automation stack
  • Silent failure identification and report
  • Top 3 automation opportunities prioritised
  • Written audit report with recommendations
Book Automation Audit →
FOR OPERATORS

Full Automation System

2–4 weeks

Map, build, and operate your entire automation layer — from lead intake to billing to ops monitoring. Multiple pipelines, unified alerting, shared monitoring dashboard, and ongoing maintenance as your processes evolve.

  • Full workflow map for all processes
  • Multiple pipelines built and tested
  • Unified Slack alert channel and runbook
  • Monthly maintenance and iteration included
Scope Full System →
⟶ The pipeline is mapped. The alert is configured.

What Are You StillDoing Manually??

Describe the process — what triggers it, what it does, where it outputs, and what happens when it fails. We will tell you whether it should be automated, how to build it, and what it will cost. No inflated quotes. No Zapier upsell.