Build Your Custom AI Automation Workflow
A custom AI automation workflow for a small business has a fixed-price build cost. The final price depends on API complexity, data sources, and business logic.
Syntora offers expertise in designing and building custom AI automation workflows for industries like Commercial Real Estate (CRE). These systems can process documents, integrate with existing platforms, and automate complex business logic. Syntora helps clients conceptualize and engineer tailored solutions to their specific operational challenges.
Scope is determined by the number of systems to integrate and the sophistication of the AI model required. For example, a simple document processor that uses the Claude API to extract data from PDFs is a typical 2-week build. An AI agent that must query a CRM, an ERP, and a shipping provider before responding generally requires a 4-week build.
What Problem Does This Solve?
Many businesses try to automate with off-the-shelf tools, but hit a wall with business-critical workflows. A platform like Airtable Automations is great for simple triggers within its own database. But it fails when you need to process an unstructured PDF attachment or call a non-standard industry API that requires OAuth2 authentication. The tool simply lacks the required function.
A common scenario is a 6-person insurance agency processing 200 claims per week from PDF forms. They might try a generic parsing tool, but its OCR engine consistently fails on handwritten notes and complex table layouts, causing a 15% error rate that requires manual review. They might try a visual workflow builder, but the cost model breaks them. A single claim might require checking the policy, assigning an adjuster, and creating a calendar event, burning 3 tasks. At 200 claims/week, that is 2,400 tasks a month, pushing them into an expensive tier for one broken workflow.
These tools are designed for connecting well-known SaaS apps with simple data structures. They are not built for the messy, specific, high-stakes processes that actually run your business. They force you to simplify your process to fit the tool, instead of building a tool that fits your exact process.
How Would Syntora Approach This?
Syntora would begin by mapping your exact manual workflow. We would use 50-100 real-world examples, such as PDF invoices or support emails, to establish a thorough test set. The initial step involves writing a Python script, often using `pdfplumber` for text extraction and the Claude API for structured data generation. This process converts unstructured documents into clean JSON that a computer can read. Our aim is to achieve high accuracy, targeting over 99% for critical fields like invoice numbers and client names. We have successfully applied this pattern in document processing pipelines using Claude API for financial documents, demonstrating its effectiveness for structured data extraction.
The core logic would be built as a FastAPI service. This Python application would contain all the specific business rules that visual workflow builders cannot handle. For instance, such a service could take extracted claim data, call a CRM's custom API using `httpx` to validate a policy, and query a Supabase table to find a suitable resource. The system would be designed for quick execution, with typical decision processes completing in milliseconds.
Syntora would deploy the FastAPI service on AWS Lambda, where it can be triggered by new files. This serverless architecture is designed to be cost-effective and scalable. For example, an application handling a moderate volume might incur AWS costs under $20 per month. We would configure `structlog` for structured logging. This ensures that if an error occurs, the exact input data and API response that caused the failure are recorded, allowing for rapid issue identification and resolution.
Finally, Syntora would integrate the output into your existing systems. The service would push processed data, assignments, and a link to the original document directly into your main management platform via its REST API. Your team would see results within their familiar tools, requiring no new software to learn.
What Are the Key Benefits?
Live in 2-4 Weeks, Not Quarters
Our fixed-scope engagements move from discovery to production deployment in 15-20 business days. You see results immediately.
Pay Once for the Build, Not Per User
We deliver your system for a single fixed price. After launch, you only pay for low-cost cloud hosting, not a recurring SaaS subscription.
You Get the Full Source Code
We transfer the complete Python source code and deployment scripts to your private GitHub repository. You own the asset, free from vendor lock-in.
Monitoring That Catches Failure First
The system includes CloudWatch monitoring and alerting. If a third-party API fails, we get an alert before your team even notices a problem.
Connects Directly to Your Core Systems
We write custom integrations for your specific CRM, ERP, or industry platform. No workarounds or intermediate databases are required.
What Does the Process Look Like?
Discovery and Scoping (Week 1)
You provide API credentials and walk us through your current process. We deliver a detailed scope document outlining the exact workflow, data fields, and logic to be built.
Core System Development (Week 2)
We build the main FastAPI service and data processing logic. You receive a link to a private GitHub repository to track progress and view the code.
Deployment and Integration (Week 3)
We deploy the system to a staging environment on your cloud infrastructure. You receive a secure endpoint to test the complete workflow with your own data.
Launch and Handoff (Week 4)
After your final approval, we move the system to production. You receive full documentation, a runbook, and 30 days of included post-launch monitoring and support.
Frequently Asked Questions
- What factors have the biggest impact on the project cost?
- The primary cost drivers are the number of external systems we need to integrate with and the complexity of the AI logic. A workflow that reads a PDF and writes to one database is straightforward. A system that needs to connect to three different APIs, each with unique authentication, and perform multi-step reasoning with Claude will have a higher fixed price and a longer timeline.
- What happens if a third-party API like Claude goes down?
- The system is built with resilience in mind. We use `httpx` with exponential backoff for transient network errors. If an API is fully down, the AWS Lambda function will automatically place the failed job into a dead-letter queue. We receive an immediate alert, and once the external service is restored, we can reprocess all the failed jobs from the queue with a single command. No data is ever lost.
- How is this different from hiring a freelancer on Upwork?
- We provide a productized service, not just hours. The engagement is a fixed-price build with a defined scope, timeline, and deliverables including production-grade logging, monitoring, and documentation. A typical freelancer provides code, but we deliver a fully operational and maintainable system. The person on the discovery call is the engineer who builds and supports the entire system.
- How is my company's sensitive data handled?
- We never store your data on Syntora's systems. The entire workflow is deployed directly within your own AWS cloud account. You grant us temporary, limited IAM access to set it up. Once the project is complete, you can revoke that access. All data processing happens on your infrastructure, under your control.
- What does the optional flat monthly maintenance plan cover?
- The maintenance plan covers proactive dependency updates (like new Python or library versions), monitoring API changes from third parties, and responding to any production alerts. It also includes a small bucket of hours for minor feature adjustments or tweaks to the business logic, ensuring the system evolves with your process.
- We don't have an engineering team. Can we still use this?
- Yes, the systems are designed to be zero-touch after launch. They run automatically and alert us if anything breaks. You do not need any technical staff. The source code and documentation are provided so that if you do hire an engineer in the future, they have everything they need to take over the system without needing to contact us.
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