Building Production-Grade Automation Beyond Visual Workflows
Reliable alternatives are custom-coded APIs and serverless functions built with production-grade engineering. These systems connect your tools directly, handle complex logic, and run on your own infrastructure.
The right approach depends on workflow intricacy and data volume. A simple multi-step process can be a small API, while a system handling real-time document processing requires a more involved event-driven architecture.
We recently built a document processing pipeline for a 12-person logistics firm. They were manually keying 800 invoices a month. We deployed an AI system using the Claude API and OCR that processes each invoice in 8 seconds, cutting a 6-minute manual task to zero.
What Problem Does This Solve?
Most businesses begin with visual automation platforms because they connect apps quickly. But their task-based pricing models become expensive as volume grows. A single new lead might trigger 5 tasks: enrichment, CRM entry, Slack notification, suppression list check, and spreadsheet logging. At 500 leads a month, this single workflow consumes 2,500 tasks, pushing you into a higher pricing tier.
Consider a 15-person e-commerce company trying to sync Shopify orders with a custom ERP. A visual builder can trigger on a new order, but it cannot handle the required logic. It needs to check inventory, apply customer-specific discounts from a separate database, and handle partial refunds. The platform's conditional paths branch but cannot merge, forcing duplicate, hard-to-maintain steps that double the task count and often time out on API calls.
These platforms also lack robust error handling and observability. When a third-party API is slow or returns an unexpected error, the entire workflow halts without a clear log of what failed. You are left with a failed run in a dashboard, no ability to retry from the point of failure, and no way to inspect the payload that caused the issue. This is not a tenable solution for business-critical processes.
How Does It Work?
We begin by mapping every process step to a specific function in Python. The Shopify new order trigger becomes a webhook received by a FastAPI endpoint. Instead of a linear sequence of tasks, we use async httpx calls to check inventory and customer data in parallel. This initial data gathering phase typically takes 3-5 business days.
The core logic is built as a state machine. A customer order with a special discount code is a different state than a standard order. This approach eliminates the branching logic issues seen in visual builders. For a recent build, we handled 12 distinct order states. We use Supabase as a lightweight database to cache API responses and store transaction logs, reducing redundant API calls by over 70%.
The final application is deployed as a serverless function on AWS Lambda. This architecture scales automatically from zero to thousands of requests without any server management. The typical P99 response time for a complex 5-step workflow is under 400ms. Monthly hosting costs for processing up to 50,000 orders are usually under $20, which is a fraction of a mid-tier no-code subscription.
We integrate structured logging using structlog, which writes JSON logs to AWS CloudWatch. If an API call to the ERP fails, the system automatically retries twice with exponential backoff. If it still fails, it sends a detailed alert to a designated Slack channel with the full request payload and error trace. This provides complete visibility, unlike the black-box history logs of most platforms.
What Are the Key Benefits?
Go Live in 2 Weeks, Not 2 Quarters
We scope, build, and deploy custom workflows in 10-15 business days. Your critical processes are fixed fast, without a long implementation cycle.
Pay for Compute, Not Tasks
Your cost is based on milliseconds of server time on AWS Lambda, not arbitrary task counts. This often reduces monthly bills by over 90%.
Your Code, Your GitHub, Your Control
We deliver the complete Python source code to your private GitHub repository. You are never locked into a platform or a vendor.
Alerts That Pinpoint Failure
When a workflow breaks, you get a Slack alert with the exact error and input data. No more digging through opaque 'run history' logs.
Connect Anything with an API
We write direct integrations to your CRM, ERP, and industry-specific platforms. No relying on a marketplace connector that lacks a key feature.
What Does the Process Look Like?
Discovery and Scoping (Week 1)
You provide API credentials and walk us through the existing process. We deliver a detailed technical specification and a fixed-price proposal.
Core Logic Development (Week 2)
We build the Python application and set up core integrations. You receive access to a staging environment to test the primary workflow.
Deployment and Testing (Week 3)
We deploy the system to production on your AWS infrastructure. You receive a runbook detailing the architecture and monitoring setup.
Monitoring and Handoff (Weeks 4-6)
We monitor the live system for 2 weeks to handle any edge cases. After this period, we transition to an optional monthly maintenance plan.
Frequently Asked Questions
- What does a typical custom build cost?
- Pricing is a fixed, one-time fee based on complexity. A simple workflow connecting two APIs might be a 2-week project. A multi-step document processing pipeline with an AI component could be 4 weeks. After the build, you only pay for cloud hosting, which is minimal. We provide a detailed quote after our initial discovery call.
- What happens if a third-party API we rely on changes?
- Our maintenance plan covers this. We build with versioned API endpoints where possible, but breaking changes happen. When they do, we get an alert from our monitoring system. We then scope the update, which is typically a few hours of work to adjust the code, test, and redeploy. This is much faster than waiting for a platform connector to be updated.
- How is this different from hiring a freelance developer on Upwork?
- Syntora provides an end-to-end service from architecture to deployment and maintenance. We build with a standardized, production-ready stack (FastAPI, AWS Lambda, structlog) that is documented and supportable. A freelancer might deliver a script, but we deliver a complete system with logging, monitoring, and a clear path for future development. You work directly with the founder and engineer.
- Do I need an engineering team to manage this after handoff?
- No. The system is designed to be self-sufficient with automated monitoring and alerting. The provided runbook covers common operational tasks. For businesses without an engineering team, we offer a flat monthly maintenance plan that covers monitoring, dependency updates, and minor changes. The goal is for you to not need to think about it.
- Can you build integrations for platforms without a modern API?
- Yes. We have built systems that interact with older SOAP APIs, FTP servers, and even systems that only export CSV files. We write the necessary adapter code in Python to translate data between legacy and modern systems. This is a common use case where visual automation platforms, which rely on pre-built REST API connectors, often fail.
- What if our business process changes after the build is complete?
- The code is yours, so it is designed to be extensible. Simple changes, like adding a new field to a CRM mapping, are included in our maintenance plan. More significant changes, like adding a new integration or a major logic branch, would be scoped as a new, smaller fixed-price project. The modular design makes these additions straightforward.
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