Production · Xentraffic · Montreal, Canada · Jan 2026 → Present

AI-Driven ERP
for Affiliate Marketing.

Xentraffic runs a CPA affiliate network out of Montreal. When I joined, 5 platforms were running in parallel with no shared data layer — every weekly report was 8 hours of manual work. I built the system that changed that.

8h → 30m
weekly reporting time
51
database tables
11
n8n workflows automated
4
LLM providers wired in

The Problem

Five platforms. Zero shared data. Eight hours lost every week.

Xentraffic was running its affiliate operations across five completely disconnected platforms: Everflow for affiliate tracking, ClickUp for task management, and BuyGoods, Digistore24, and ClickBank for product catalogs and sales data.

Every Monday, someone spent 8 hours manually pulling data from each source, consolidating it in spreadsheets, and building a report that was already out of date by the time it was finished.

Fraud detection was nonexistent. High-risk affiliates were generating fake traffic and fraudulent conversions with no automated signal to catch them. By the time the pattern was visible, commissions had already been paid.

Everflow

Affiliate tracking, clicks, conversions, payouts

ClickUp

Tasks, documents, team operations

BuyGoods

Product catalog + sales (CSV-only API)

Digistore24

European product catalog + analytics

ClickBank

Affiliate marketplace + revenue data

Architecture

AI doesn't work in one layer. It works in three.

Most teams think "adding AI" means adding a chatbot. The real leverage is in stacking all three layers — each one building on the one below it.

01

Embedded Intelligence

The system calculates, automatically.

Affiliate scoringGold / Silver / Bronze tiersSmart Match recommendationsDNA category tagsReliability scoreIP fraud detection
02

Operational Automation

The system acts, without human input.

11 n8n workflowsHourly fraud scanAuto-suspend on Everflow APITelegram approval for medium riskDaily Slack AI reportEPC drop alerts
03

Conversational AI

The system speaks your business language.

Text-to-SQL on 51 tables4 LLM providersSlack AI agentAutomated daily reportsSQL safety validatorAI observability + cost tracking

What I Built

Six systems, one unified platform.

Text-to-SQL Query Engine

Layer 3

Any team member types a question in plain English — the engine generates safe, read-only SQL, runs it against 51 live tables, and returns a formatted answer. Built a multi-provider LLM gateway (Claude, OpenAI, Gemini, Groq) with semantic caching, rate limiting, and full observability.

Fraud Detection Pipeline

Layer 2 + 3

Runs hourly via n8n on live Everflow data. Detects CR spikes, duplicate click floods, dead sub1 sources, and bot traffic patterns. High-risk affiliates are auto-suspended via the Everflow API. Medium-risk → Telegram alert with one-tap approve/suspend. High-risk → auto-action, no human needed.

Affiliate Intelligence

Layer 1

Automatic Gold/Silver/Bronze tiering based on lifetime revenue. Reliability score calculated daily from conversion rate, revenue, and issue history (refunds, disputes). Smart Match recommends offers an affiliate isn't promoting yet but that match their top-performing categories.

Multi-Platform CRM

Layer 1

Synchronized product catalogs from ClickBank, Digistore24, and BuyGoods (including a custom CSV import pipeline with 7-step codename resolution for BuyGoods, which has no usable public API). Visual Flow Builder for sales funnels with drag-and-drop upsell/downsell design.

Daily AI Report to Slack

Layer 2 + 3

Every morning at 9:00 AM, an n8n workflow pulls Everflow stats, affiliate data, and product analytics — sends them to an LLM — and posts a structured business brief to Slack. 365 reports a year, zero human effort.

Observability Stack

Infrastructure

Prometheus + Grafana for API and infrastructure metrics. AI-specific observability in MySQL via ObservabilityService — tracks cost per request, latency, cache hit rate, token usage, and error rate for every LLM call. PM2 + Nginx + GitHub Actions CI/CD in production.

Stack

Every choice was deliberate.

Frontend

Next.js 14
React 19
TypeScript
Tailwind CSS

Backend

Node.js 20
Express.js
MySQL 8
DigitalOcean

AI / LLM

Claude API
OpenAI
Groq
Google Gemini

Automation

n8n (self-hosted)
node-cron
GitHub Actions
PM2

Integrations

Everflow API
ClickBank API
Digistore24
ClickUp API

Observability

Grafana
Prometheus
Node Exporter
Swagger UI

What Was Actually Hard

The problems nobody talks about.

Problem

BuyGoods has no usable API

How I solved it

Built a 7-step CSV/XLS importer with auto-format detection, column mapping, and a codename catalog to resolve product identifiers that differ between export formats. Handles edge cases where BuyGoods changes their column headers between exports.

Problem

ClickBank API blocks Algerian DNS

How I solved it

Monkey-patched Node.js dns.lookup to fall back to DNS-over-HTTPS via Cloudflare when direct resolution fails for clickbank.com domains. Results are cached to avoid repeated DoH calls. This is the kind of problem that costs 2 days if you don't know what's happening.

Problem

Text-to-SQL safety on a production database

How I solved it

Built SQLValidator that blocks every destructive operation (INSERT, UPDATE, DELETE, DROP, ALTER, TRUNCATE) before execution. The AI agent is strictly read-only. Combined with rate limiting (10 req/min per user) and a complete audit log in ai_query_logs.

Problem

Fraud detection that acts before the commission window closes

How I solved it

Most fraud tools flag after the fact. Built an hourly n8n pipeline that checks live Everflow traffic, runs ML scoring, and auto-suspends high-risk affiliates via the Everflow API — before the daily validation cycle processes payouts.

Results

Numbers that matter.

8h → 30m
weekly reporting time
500+
affiliates managed automatically
11
workflows replacing manual tasks
365/yr
AI reports generated, zero effort

The ERP went from idea to production in 4 months, running on a DigitalOcean Droplet with PM2 + Nginx + GitHub Actions CI/CD. The team went from spending an entire Monday on reporting to getting an AI-generated brief in Slack every morning at 9 AM.

Need something like this?

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