Data & AI
Business process automation: reliable workflows, integrations and scripts
Automation means having machines carry out the repetitive tasks that connect your applications: syncing contacts between a form and the CRM, generating invoices, sending notifications, producing reports, moving files, following up with customers. It does not require artificial intelligence: most of the gains come from simple rules executed reliably.
This service is for businesses whose teams re-enter data, export spreadsheets by hand or watch mailboxes to trigger actions. Together we choose between platforms such as n8n, Make or Zapier, and custom code, depending on volume, criticality, the need for control and long-term cost.
What separates an automation that lasts from one that breaks after three months is the details: secured webhooks, idempotency so no duplicates are created when an event arrives twice, retries with exponential backoff, API quota handling, alerts on failure and readable logs. This is what we put in place systematically.
When do we step in?
Re-entering data across several tools
The same information is typed into the CRM, the invoicing tool and the tracking spreadsheet. An API or webhook integration keeps these systems in sync and removes copy errors.
Reports produced by hand
Every week, someone exports data, assembles it in a spreadsheet and sends an email. A scheduled job queries the sources, generates the report and distributes it automatically.
Missing notifications and alerts
A large order, a failed payment or low stock should trigger a Slack, Teams or SMS notification. Today, the information is discovered too late.
Zapier or Make becoming costly or fragile
Your scenarios have multiplied, the bill climbs with the number of operations and nobody knows who created what anymore. It is time to rationalize, migrate to self-hosted n8n or move some parts to code.
Recurring file processing
Files received by SFTP or email to import, images to resize, documents to generate as PDF: these treatments call for robust scripts with error handling, not manual operations.
How we work
- 1
Process inventory
We list repetitive tasks, their frequency, the tools involved, the edge cases and the current cost in time. We prioritize by gain and feasibility.
- 2
Choice of approach
A platform (n8n, Make, Zapier) for simple flows your teams can edit, custom code (Python, Node.js) for high volumes, critical processing or complex integrations. Often a mix of both.
- 3
Flow design
Triggers (webhooks, schedules, events), transformations, error handling, idempotency, retries, API rate limits, and what happens when a system is unavailable.
- 4
Development and testing
Implementation on a test environment with realistic data, error case testing, secrets stored securely, documentation of every flow.
- 5
Production and monitoring
Gradual rollout, alerts on failure, execution dashboards, and regular review to adapt flows when your tools or processes change.
Technologies we use
- n8n
- Make
- Zapier
- Python
- Node.js (TypeScript)
- Webhooks and REST APIs
- Scheduled jobs (cron, Amazon EventBridge)
- Message queues (BullMQ, Celery, SQS)
- AWS Lambda
- Google Workspace and Microsoft 365 (API)
- Slack and Teams (API)
Related expertise
Why choose Agencei?
The right tool, not our tool
We have no interest in selling you a platform. If Make is enough, we say so; if volume or criticality call for code, we build it.
Robust from the start
Idempotency, retries, quota handling, alerts: we design for error cases, because that is where makeshift automations end up costing more than they save.
Understanding of business APIs
We regularly integrate CRMs, invoicing tools, ERPs, e-commerce platforms and payment services, and we know their rate limits, webhooks and quirks.
Handover and autonomy
Every flow is documented and, whenever possible, designed so your teams can adjust it without us.
In brief
- What is this service?
- Business process automation service: workflows between applications, API integrations, scripts, scheduled jobs and notifications, with n8n, Make, Zapier or custom code.
- Who is it for?
- SMEs, mid-sized companies, e-commerce businesses and software vendors whose teams re-enter data, produce reports by hand or manually watch for events across several tools.
- What problem does it solve?
- Time lost on repetitive tasks, copy errors, information discovered too late, existing automations that are fragile or costly.
- How long does it usually take?
- A simple flow is set up in a few days. A set of integrations between several systems usually takes a few weeks. Rationalizing an existing portfolio of automations is often measured in weeks.
- What factors influence the price?
- Price depends on the number of flows and systems, the quality of the APIs involved, the volume processed, the choice between platform and code, security requirements and the desired monitoring.
- How does the engagement run?
- Inventory and prioritization, choice of approach, flow design with error handling, development and testing, monitored production rollout and regular review.
- What are the risks?
- Duplicates created by repeated events, silent failures, exceeded API quotas, poorly protected secrets, platform costs climbing with volume, undocumented flows nobody understands.
- What alternatives exist?
- Native integration features of your software, training teams on Zapier or Make for simple flows, or developing a module integrated into your application.
Frequently asked questions
n8n, Make, Zapier or custom code: how do we choose?
Zapier and Make are quick to set up and accessible to non-developers, but their cost grows with volume and control is limited. n8n, which can be self-hosted, offers more freedom and predictable cost, at the price of operating it. Custom code is required for high volumes, critical processing, complex logic or security requirements. We choose based on your context, and we often combine them.
What happens when an automation fails?
A well-designed automation retries automatically on temporary errors, does not create duplicates if an event is received twice, and alerts a person if the problem persists. Executions are logged so you can understand what happened and replay if needed.
Do we need artificial intelligence to automate?
No, in most cases. Explicit rules are more reliable, cheaper and easier to verify. AI becomes useful when language or unstructured documents need to be interpreted; we add it at that point, on the relevant step only.
Is our data safe on these platforms?
Hosted platforms process your data on their servers, under their terms and in their location. For sensitive data or data subject to GDPR, we favor self-hosted n8n or code deployed in your infrastructure, with securely stored secrets and restricted access.
Can you take over existing automations?
Yes. We audit the existing scenarios, identify duplicates, weak points and costs, then rationalize: consolidation, migration to another platform or rewriting in code for the critical parts.
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