Automate Core Business Processes with Custom AI

Many teams start with IFTTT for simple triggers, but it fails on any real business logic. It has no error handling or retry logic, so a single API outage breaks the entire chain silently, with no notification.

Platforms like Zapier handle more steps but their per-task pricing model is costly for high-volume processes. A workflow to read an email, extract an attachment, parse its text, and add a row to a Google Sheet burns four tasks per email. At 50 invoices a day, that is 200 tasks daily and a $100+ monthly bill for one workflow. The five-minute polling interval on many triggers also means your data is never real-time.

A regional insurance agency with 6 adjusters tried to automate claim intake. Their workflow failed whenever a submitted PDF was a scanned image instead of text, because the platform's built-in parser could not read it. The workflow required manual checks of a failure log, which defeated the purpose of automation. These platforms are not development environments; you cannot add an OCR step, manage state, or implement robust logging when things break.

Syntora would begin by integrating directly with your source systems, typically via IMAP for email or a webhook for services like Zendesk. We would use the Python `imaplib` for email polling and deploy a FastAPI endpoint to receive webhook data. For critical workflows requiring faster intervals than standard platform polling, an AWS Lambda function can be set up to trigger checking an inbox every 60 seconds.

The core logic for document processing often involves a state machine written in Python. For a document like a claims PDF, the system would first attempt to extract text using `PyMuPDF`. If that indicates a scanned image, the workflow would route it to AWS Textract for optical character recognition (OCR). The Claude 3 Sonnet API would then be used to extract key entities, such as policy numbers and claimant names, with a Pydantic model providing robust response validation. This approach offers far greater reliability than traditional regex-based parsers.

Processed data would then be sent to your target system. Rather than relying on generic connectors, Syntora would develop a dedicated client using `httpx` to interact with your system's REST API. This allows for custom error handling, including multi-attempt retries with exponential backoff if an API is temporarily unavailable. The entire application would be packaged into a Docker container and deployed on AWS Fargate for continuous, scalable operation. Typical hosting costs for such a system are under $50 per month.

Syntora would implement structured logging with `structlog` and pipe logs to a monitoring service like Datadog. We would configure alerts for specific failure conditions, such as the Claude API returning validation errors on more than 5% of documents within an hour. This ensures real-time visibility into the system's health. From initial discovery to full deployment, projects of this complexity typically take 3-4 weeks, assuming clear requirements and client data access.