Build Internal AI Agents to Automate Your Operations

Many small businesses start with visual workflow builders. These tools are great for simple triggers, like posting a Slack message when a new lead arrives in HubSpot. But business-critical processes are rarely that simple. These platforms fail when logic gets complex or when reliability is essential.

A common failure point is task-based pricing. A workflow that reads an attachment, summarizes its content, checks for keywords, and saves the output to a database can consume four tasks for a single document. Processing 500 documents a month results in 2,000 tasks and a surprisingly high bill for one automated process.

Consider an operations team that needs to process vendor invoices. The workflow must open a PDF, extract the invoice number and amount, match it to a PO in their accounting software, and flag any discrepancies over 10%. A point-and-click tool's branching logic often requires duplicating steps, doubling task counts. If the accounting software's API is slow, the workflow times out with no automatic retry, forcing a manual check of every invoice.

Syntora's engagement begins with a comprehensive audit of your manual workflows, breaking them down into discrete steps. We translate these steps into a series of Python functions, opting for custom code over visual editors to ensure maximum control, flexibility, and maintainability. All solutions are designed for deployment on your own cloud infrastructure, providing you with full ownership over logic, error handling, and operational costs.

For internal task automation, Syntora would typically design a resilient system around a FastAPI service. This service would expose a single, secure endpoint to receive inputs, such as newly uploaded documents or triggered events from existing systems. AWS Lambda functions would handle event processing, extracting text from documents, sending it to the Claude API for advanced summarization or data extraction, and then storing the structured output in a Supabase database. This architecture is chosen for its scalability, cost-efficiency, and robust integration capabilities.

Robust error handling is a core component of any system we deliver. Instead of failing an entire workflow, the system would include specific logic to manage malformed documents or API timeouts from external services. Errors would be logged in Supabase and generate targeted alerts, such as Slack notifications, allowing for efficient exception management without constant manual intervention.

The delivered system would expose a user-friendly dashboard, typically deployed on Vercel, to provide a clear overview of processed documents, their status, and any items flagged for review. Role-based access control would be managed through Supabase Auth to ensure secure and appropriate access for your team. A typical engagement for a system of this complexity involves a build timeline of 8-12 weeks, requiring access to historical data for thorough testing and validation. Clients would need to provide detailed workflow documentation, sample data, and access to relevant internal systems for integration during the discovery and development phases.