Get Production AI in 4 Weeks Without Hiring an Engineer
Hiring an AI consultancy delivers production-ready systems in weeks without long-term payroll commitment. Building an in-house team provides dedicated resources but requires months of hiring and onboarding.
Syntora offers AI automation consultancy services, focusing on expertise and engineering engagements. We describe technical architectures and our proposed approach for building solutions in detail, demonstrating our capability without relying on fabricated project histories.
For many organizations, the decision between an AI automation consultancy and an in-house team centers on balancing speed-to-solution against long-term resource investment. A consultancy offers specialized expertise with a defined scope and predictable costs, while an in-house hire provides internal control but introduces risks of a prolonged talent search, high salaries, and uncertain delivery timelines. Syntora provides deep technical architecture and engineering capability to address complex automation needs, focusing on efficient project delivery.
What Problem Does This Solve?
Small businesses often consider hiring a full-time engineer to build AI systems. The first obstacle is the 3-to-6 month search to find a qualified candidate, followed by a $150,000+ salary. The person you hire is often a generalist who is skilled in analysis but has never deployed a production API with monitoring and logging. They spend their first quarter learning your business and setting up basic infrastructure, not building the tool you need.
A 20-person insurance agency hired a data scientist to automate claim triage. The new hire spent two months building a model in a Jupyter notebook that worked on their laptop. But they did not know how to deploy it as a scalable API on AWS, set up automated retries for failed jobs, or integrate it with their existing claims management software. The project stalled, and the business was paying a full-time salary for a system that never went live.
This single-person dependency creates immense risk. If your one engineer gets sick, goes on vacation, or quits, development halts. There is no one for code review, architectural guidance, or emergency support. The business becomes reliant on a black box system that nobody else understands, making future updates or fixes nearly impossible.
How Would Syntora Approach This?
Syntora would begin an engagement with a focused discovery phase to understand your organization's specific workflows and define tangible success metrics. This initial step involves detailed mapping of current processes, from data intake to platform integration, to establish clear project requirements and expected outcomes. The objective is to produce a formal technical specification that outlines the proposed architecture and data flow before any development, ensuring alignment with your precise operational needs.
The core of a document processing system typically involves a Python service built with FastAPI, designed to expose a clean and efficient API layer. For intelligent data extraction from documents, the Claude API would be employed, coupled with pydantic for strict data validation. This architecture ensures that extracted fields, such as policy numbers or invoice dates, adhere to predefined formats and business rules. Syntora has extensive experience building document processing pipelines using the Claude API for financial documents, and the same robust pattern would apply to your specific document types. A production-ready service of this complexity can often be developed efficiently, focusing on clarity and maintainability.
Deployment of the FastAPI service would utilize containerization on AWS Lambda to ensure high availability and cost-effectiveness. This setup is designed to scale with demand, handling varying document volumes efficiently. Supabase would be integrated for storing processing history, managing user credentials for internal dashboards, and maintaining an audit trail. The entire infrastructure for the system would be defined as code, allowing for version control, simplified replication across environments, and clear documentation.
Upon the successful completion of the engagement, Syntora would transfer the full source code to your company's designated GitHub repository. Deliverables would include a detailed runbook with setup instructions, API documentation automatically generated by FastAPI, and a guide for monitoring system logs within AWS CloudWatch. This approach ensures your complete ownership of the intellectual property and provides you with the necessary tools for ongoing operation and control of the system on your infrastructure. A typical project of this nature, from discovery to deployment and handover, could range from 8 to 16 weeks depending on the complexity of documents and integrations.
What Are the Key Benefits?
Production System in 20 Business Days
An in-house hire spends their first month onboarding. We deliver a complete, production-ready system in that same timeframe, ready for immediate business use.
Fixed Price Build, Not a Full-Time Salary
Avoid the $150k+ annual cost, benefits, and equity of a senior engineer. You get the specific result you need with a single, scoped project investment.
You Get the Keys and the Blueprints
We deliver the complete Python source code to your GitHub. You own the asset, free from vendor lock-in or recurring per-seat licensing fees.
Alerts Go to Us, Not Your Inbox
Our optional maintenance plan includes uptime monitoring via AWS CloudWatch and structured logging with structlog. If an API call fails, we know before you do.
Connects Directly to Your Core Systems
We build direct integrations to your CRM, ERP, or industry platforms using their native APIs. This avoids third-party connectors that add latency and another point of failure.
What Does the Process Look Like?
Week 1: Scoped System Design
You provide workflow details and API credentials for your existing tools. We deliver a technical design document outlining the full architecture, data models, and a fixed-price quote.
Week 2: Core Logic Build
We write the production code in Python. You get access to a private GitHub repository to track progress and review the code as it is written.
Week 3: Deployment and Testing
We deploy the system to your cloud infrastructure. You receive a staging environment to test the full workflow with real data before the production launch.
Week 4: Handoff and Monitoring
The system goes live. We deliver the final source code, documentation, and a runbook. We monitor system performance for 30 days post-launch to ensure stability.
Frequently Asked Questions
- How is the fixed price determined?
- Pricing is based on three factors: the number of systems to integrate, the complexity of the business logic, and the quality of the source APIs. A single document type from a modern API is a 2-week build. Processing multiple document types from a legacy system is a 4-week build. We provide a firm quote after our discovery call.
- What happens if an external API like Claude is down?
- We build in default fallbacks and automated retry logic. If the Claude API fails, the system will retry 3 times with exponential backoff. If it still fails, the job is flagged for manual review and a notification is sent to a specific Slack channel. Your core business process never halts unexpectedly.
- How is this different from hiring a freelancer on Upwork?
- Freelancers often deliver scripts, not maintainable systems. We build production-grade software with logging, monitoring, and automated deployment. We deliver full source code and documentation, whereas many freelance engagements end with a script only the original developer understands. We also offer optional ongoing maintenance plans for long-term support.
- Who handles the ongoing cloud costs?
- The system is deployed on your own AWS account, so you pay the infrastructure costs directly. We design for cost-efficiency; a typical automation system costs less than $100 per month to run. You have full transparency and control over these expenses, with no markup from us. You see the bill directly from AWS.
- What if we need to make changes later?
- You own the source code, so any Python developer can make changes. The code is clean, documented, and follows standard practices. For clients on our maintenance plan, we can scope and build new features as small, fixed-price follow-on projects. Most feature additions are scoped as 1-week builds.
- What kind of access do you need to our systems?
- We require temporary, scoped-down API keys or service account credentials for the specific systems we integrate with, such as read-only access to a CRM. We never ask for full administrator logins. All credentials are stored securely and you can revoke access upon project completion. We provide a checklist of all required permissions during kickoff.
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