[01] system: healthy
[02] observer: active
[03] infrastructure: stable
[04] uptime: 99.99%
[05] connections: secure
[06] monitoring: enabled
[07] alerts: configured
[08] status: operational
status: operational [OK]
alerts: configured [OK]
monitoring: enabled [OK]
connections: secure [OK]
uptime: 99.99% [OK]
infrastructure: stable [OK]
observer: active [OK]
system: healthy [OK]
import { FlowGuard } from '@basecore/flowguard';
import { WhatsAppEngine } from '@basecore/engine';

const observer = new FlowGuard({
  n8n: process.env.N8N_URL,
  alerts: {
    channel: 'whatsapp',
    operator: config.operator
  }
});

observer.on('anomaly', async (signal) => {
  await notify(signal.context);
  // Human decides next action
});

const engine = new WhatsAppEngine({
  tenant: config.tenantId,
  isolation: true
});

await engine.connect();
console.log('Infrastructure ready');

Illustrative example of Basecore Labs products running in the client's environment.

Infrastructure for Production Teams

Infrastructure for teams that operate in production.

Basecore Labs is a software lab dedicated to creating infrastructure products for real technical operations β€” where predictability, clarity, and accountability are essential.

Production-grade reliability

Metrics observed in production environments using Basecore Labs products.

prod-engine-01
online
WhatsApp Engine β€’ us-east
flowguard-main
online
FlowGuard β€’ eu-west
prod-engine-02
online
WhatsApp Engine β€’ sa-east
observer-node
online
FlowGuard β€’ us-west
prod-engine-03
online
WhatsApp Engine β€’ ap-south
flowguard-backup
online
FlowGuard β€’ eu-central
prod-engine-04
online
WhatsApp Engine β€’ ap-northeast
monitor-cluster
online
FlowGuard β€’ us-central
99.9%
Uptime
<5min
Avg. MTTR
10K+
Incidents Prevented
50K+
Workflows Monitored

Data from client environments. Basecore Labs does not operate these systems.

The reality of automation in production

Most automation infrastructure wasn't designed for production reliability

Automation Fragility

Workflows break silently. Dependencies change. APIs timeout. Without proper observability, you only know something failed when users complain.

Silent Failures

Executions complete with errors buried in logs. Partial successes mask data inconsistencies. By the time you notice, damage is already done.

Lack of Predictability

No baseline metrics. No anomaly detection. No way to know if today's 3-minute execution is normal or a sign of degradation.

SaaS Constraints

Vendor lock-in. Limited customization. Data leaving your infrastructure. When reliability matters, you need control over your stack.

Why Basecore Labs exists

Modern systems have grown rapidly. Automations, integrations, and messaging now sustain critical operations.

However, the infrastructure needed to keep these systems reliable hasn't evolved at the same pace.

Basecore Labs exists to address exactly this point. We develop infrastructure products that help teams structure technical operations reliably, predictably, and sustainably.

Basecore Labs develops infrastructure. Execution and operation always happen in the client's environment.

Reliability

Systems that work consistently, every time, without surprises.

Predictability

Know what's happening before it becomes a problem.

Human Control

Technology informs. People decide. Always.

Engineering over Marketing

Products built by engineers, for engineers.

Products developed by Basecore Labs

Infrastructure for technical operations. Execution in the client's environment.

WhatsApp Engine

A Basecore Labs product

WhatsApp Engine is a self-hosted WhatsApp infrastructure, designed to operate in the client's environment, with focus on stability, isolation, and operational control.

All operation occurs in the client's environment. Basecore Labs does not operate, host, or control sessions.

  • QR Code provisioning β€” connection in seconds
  • One number per tenant with complete isolation
  • Multi-tenant architecture ready for scale
  • Self-hosted β€” data stays in your infrastructure
  • Full operator control over sessions and settings
  • No dependency on Basecore external services

FlowGuard

A Basecore Labs product

FlowGuard is a product focused on observability for n8n automations. It transforms technical executions into understandable signals, helping teams identify operational risks with clarity.

"Transform fragile automations into reliable infrastructure."

FlowGuard observes and communicates. It never executes actions automatically. The decision always remains with the human operator.

  • Collects n8n executions in real-time
  • Analyzes patterns and identifies anomalies
  • Distinguishes noise from real risk
  • Communicates alerts via WhatsApp with context
  • AI only explains and guides β€” never executes
  • Human always in control of decisions
WhatsApp Engine

How WhatsApp Engine works

Self-hosted infrastructure for production-grade WhatsApp connectivity

01

QR Provisioning

Tenant scans QR code in admin panel. Connection established in seconds.

02

Session Binding

WhatsApp session bound to specific tenant. Complete isolation guaranteed.

03

Infrastructure Layer

Engine manages sessions, queues, retries, and rate limiting automatically.

04

Security & Compliance

End-to-end encryption preserved. Self-hosted β€” your data never leaves your infra.

05

Multi-tenant Ready

One number per tenant. No cross-contamination. Scale horizontally.

Your infrastructure, your data, your control. WhatsApp Engine is fully self-hosted.

How FlowGuard works

Event-driven architecture designed for observability, not execution

Collection

Captures executions, events, errors, and timing data from n8n in real-time

Analysis

Analyzers process raw data to generate signals β€” anomalies, patterns, regressions

Decision

Domain core evaluates signals to distinguish real risks from noise

Communication

Alert engine delivers contextual notifications via WhatsApp

Human

Operator receives explanation and decides on action. AI never executes automatically

FlowGuard observes and communicates. It never modifies your workflows.

Technical use cases

Real scenarios where observability makes the difference

Duration Regression Detection

Input:Workflow execution times collected over baseline period
Output:Alert when execution exceeds statistical threshold
Catch performance degradation before it impacts downstream systems

Intermittent Failure Patterns

Input:Execution success/failure sequences with error context
Output:Pattern recognition for recurring failure modes
Identify flaky integrations and unstable dependencies

Operator Alerting

Input:Classified signal from decision layer
Output:WhatsApp message with context and suggested actions
Right person notified with right information at right time

Execution Audit Trail

Input:All workflow executions with full payload data
Output:Searchable history with filtering and export
Compliance, debugging, and post-incident analysis

Anomaly Explanation

Input:Detected anomaly with surrounding context
Output:AI-generated technical explanation via WhatsApp
Understand issues without digging through logs

Multi-Workflow Correlation

Input:Execution data across related workflows
Output:Dependency mapping and cascade failure detection
See how one failure propagates through your automation

Technical FAQ

Answers to common engineering questions

Talk directly with our engineering team

No sales people. No forms. Just engineers who built this infrastructure and can answer your technical questions.

Talk to engineering

We typically respond within a few hours