Replace Fragile Workflows With Production-Grade Code
Transitioning to custom code provides limitless complexity, lower operating costs, and full system ownership. It handles high-volume tasks and complex logic that visual workflow builders cannot reliably support.
Syntora offers expert engineering services to transition repetitive data entry and document processing workflows from visual builders to robust custom code. This approach provides limitless complexity, lower operating costs, and full system ownership for business-critical processes. Syntora leverages technologies like FastAPI, Claude API, and AWS Lambda to build scalable, automated solutions.
A custom solution is ideal for business-critical processes where errors are costly. This applies to workflows with multiple conditional steps, advanced API error handling, or high-volume triggers, such as processing hundreds of form submissions or documents daily. It is not intended for simple Slack notifications or personal productivity tasks.
Syntora specializes in designing and building robust automation for complex data entry workflows. We've built document processing pipelines using Claude API for financial documents, and the same robust patterns apply to automating repetitive data extraction in any industry. A typical engagement for this type of system would take 6-12 weeks, depending on the number of data fields, source document formats, and target systems. Clients would need to provide detailed workflow documentation and access to relevant APIs for integration.
What Problem Does This Solve?
Most teams start with visual builders because they connect a CRM to a spreadsheet in minutes. But these platforms charge per task. A workflow that triggers on a new lead, enriches it via an API, checks for duplicates, and then routes it based on three conditions can burn 5-7 tasks per lead. At 150 leads per day, that is over 1,000 tasks and a bill that grows directly with your business.
A regional insurance agency with 6 adjusters used a workflow builder to process new claims from a web form. The form data needed to be cross-referenced with their policy database and then assigned. The builder’s conditional paths could branch but not merge. To check both policy type and adjuster availability, they had to create duplicate, parallel branches. This doubled the task count and made the workflow a tangled diagram that only one person understood. When an API call in one branch failed, the entire workflow halted silently, leaving claims unprocessed for days.
These tools are designed for linear, stateless tasks. They cannot maintain state, handle nuanced retries, or execute custom data transformations. You cannot write a Python function to parse a non-standard PDF or manage a transaction across two different APIs. You are limited to the pre-built actions, which means your critical business logic lives inside a fragile, third-party user interface.
How Would Syntora Approach This?
Syntora would begin an engagement by comprehensively mapping the client's entire manual data entry process. This discovery phase involves identifying every field, every decision point, and every system involved in the current workflow. Following this, we would develop a detailed technical specification. This blueprint would define the data schema, typically using a Supabase database, and outline the exact API endpoints for integration with the client's existing platforms, such as claims management or policy systems.
The core logic of the automation would be written in Python using FastAPI to create a robust API service. Instead of visual branches, standard control flow (if/else, match statements) would handle the routing logic efficiently. For external API integrations, we would utilize the httpx library for asynchronous calls, incorporating exponential backoff and retry logic. This ensures that temporary failures from external systems do not halt the entire process. All events within the system would be logged using structlog for easy debugging and auditing.
The FastAPI application would be containerized and deployed on AWS Lambda. This serverless architecture means the client would only pay for the specific compute time each data entry task requires, rather than for an idle server. A new form submission or document upload would trigger the Lambda function via an API Gateway webhook. The system would expose a clean API for other internal systems to integrate with, facilitating further automation.
We would configure comprehensive monitoring using AWS CloudWatch. This includes setting up alerts for an elevated error rate over a defined period or for any single invocation exceeding a specified duration, providing real-time visibility into system health and performance. The deliverables for such an engagement include the deployed, tested system, complete source code, detailed technical documentation, and an operating guide.
What Are the Key Benefits?
Finish in 8 Seconds, Not 6 Minutes
The system process tasks like document extraction and data validation in seconds. A 6-minute manual data entry task we automated for a recruiting firm now completes in under 10 seconds.
Pay for Compute, Not Per Task
A single, fixed-price build with minimal monthly hosting costs, often under $50. Stop paying per-task fees that penalize you for growing your business.
You Own the Code and Infrastructure
You receive the full Python source code in your GitHub repo and the system runs in your cloud account. There is no vendor lock-in. You own the asset.
Get Alerts Before Your Users Notice
We build in monitoring with AWS CloudWatch and structured logging with structlog. You get an alert if error rates spike, so issues are fixed before they impact operations.
Connect Any API, Not Just a Preset List
We write custom integrations to any platform with an API, including CRMs, ERPs, and industry-specific software. No more waiting for a connector to be added to a marketplace.
What Does the Process Look Like?
Scoping and Discovery (Week 1)
You provide documentation of the current workflow and grant read-only access to relevant systems. We deliver a detailed technical specification and a fixed-price proposal.
Core System Build (Weeks 2-3)
We write the Python code for the core logic, build the API integrations, and set up the database. You receive access to a private GitHub repository to track progress.
Deployment and Testing (Week 4)
We deploy the system to your cloud infrastructure and run end-to-end tests with production-like data. You receive a runbook detailing how to operate and monitor the system.
Monitoring and Handoff (Post-Launch)
We monitor the system for 30 days post-launch to address any issues. After this period, we hand over full control or transition to an optional flat-rate monthly maintenance plan.
Frequently Asked Questions
- How much does a custom data entry automation system cost?
- The cost depends on the number of systems to integrate and the complexity of the data transformation logic. A system connecting a web form to a CRM with simple validation may take 2 weeks. A multi-step process involving OCR, data enrichment from three APIs, and complex business rules typically takes 4 weeks. We provide a fixed-price quote after the discovery phase. Book a discovery call at cal.com/syntora/discover to discuss pricing.
- What happens when an external API the system depends on goes down?
- We build in retry logic with exponential backoff for all external API calls. If an API is down for an extended period, the failed task is sent to a dead-letter queue and an alert is triggered. This prevents data loss and allows for manual reprocessing once the external service is restored. Your core workflow is not blocked by a temporary outage.
- How is this different from hiring a freelancer on Upwork to write a script?
- A freelancer delivers a script. Syntora delivers a production system. This includes structured logging, automated testing, infrastructure-as-code for deployment, monitoring, alerting, and a runbook for maintenance. We build for reliability and handoff, ensuring the system is maintainable long after the initial build is complete. You are buying an operational asset, not just a piece of code.
- What do we need to provide to get started?
- You need to provide clear documentation of the manual process, including any edge cases. We will also need API keys or service account credentials for the systems we need to connect to. The person on your team who best understands the current process should be available for a 1-hour discovery call and for testing during the final week.
- Do we need our own AWS account?
- Yes. We deploy all infrastructure within your own AWS account. You have full ownership and control over the resources and billing. We provide the infrastructure-as-code scripts so you can redeploy or modify the environment independently. This avoids any dependency on Syntora's infrastructure.
- How do you handle sensitive data like PII?
- All data processing occurs within your own cloud environment, never on Syntora's systems. We follow best practices for handling secrets and credentials using services like AWS Secrets Manager. We can also work with you to ensure the system architecture complies with specific data privacy requirements if needed for your industry.
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