Build a CRA-Compliant AI System Before the 2026 Deadline
Syntora is not a no-code platform; we build custom AI systems that are CRA-ready. The system provide immutable audit trails and run in your private cloud for compliance.
Syntora offers expertise in designing CRA-ready AI systems for EU compliance. We provide engineering engagements to help organizations meet strict security and reporting requirements for their AI deployments. Our approach focuses on architecting auditable, private cloud solutions tailored to specific risk categories.
The EU Cyber Resilience Act (CRA) imposes strict security and reporting requirements on any AI system operating in the EU. The scope of your compliance depends on your system's risk category. A high-risk system, like one used for hiring or credit scoring, requires a third-party conformity assessment, while lower-risk systems can be self-assessed.
Developing a CRA-ready system involves tailoring the architecture to your specific risk classification and operational environment. We've built document processing pipelines using Claude API for financial documents, and the same architectural patterns for auditable, secure AI apply to meeting CRA requirements. Syntora engages with clients to design, build, and deploy these specialized systems.
What Problem Does This Solve?
Many off-the-shelf AI platforms are architecturally incompatible with CRA requirements. They run on multi-tenant infrastructure, meaning your data is processed on the same servers as other customers. This makes it impossible to guarantee data isolation or prove to an auditor that a vulnerability in another tenant’s application cannot affect you. You have no control over the underlying software dependencies, so you cannot conduct the continuous vulnerability scanning the CRA mandates.
A 20-person fintech startup used a popular AI-powered ID verification SaaS. When preparing for the CRA, they realized the vendor could not provide granular logs for every verification decision. The vendor's own SOC 2 report was not enough; the CRA puts the onus on the startup, the 'manufacturer', to prove their specific implementation is secure. They could not produce logs showing who accessed data, what model version was used, or why a specific verification failed, all of which are required for a conformity assessment.
These platforms trade control for convenience. For non-critical tasks, this is a good trade. For business-critical AI systems that fall under CRA regulation, relying on a vendor's black-box platform creates unacceptable compliance risk. You cannot delegate your responsibility as the manufacturer.
How Would Syntora Approach This?
Syntora would begin an engagement with a detailed gap analysis. This involves mapping each applicable requirement from CRA Annex I to specific technical controls and architectural patterns. The goal is to design a system where compliance is fundamental to its operation.
For robust auditability, the system architecture would ensure that every AI decision, data access event, and configuration change is logged. We would design this logging mechanism using a dedicated, immutable table in a service like Supabase, configured for structured JSON logs and row-level security. Log retention policies would be configurable to meet your specific compliance needs.
The core system would be a Python application, leveraging the FastAPI framework for API development. Pydantic is crucial for data validation, ensuring all inputs are correctly structured and rejecting malformed requests at the entry point. For logging within the application, structlog would be used to produce machine-readable JSON objects for each entry. These logs would include essential details like model version, user ID, and a unique request ID, forming the basis of the CRA-required audit trail.
Deployment would be within your private cloud environment, typically leveraging serverless platforms like AWS Lambda. This architecture ensures data remains within your infrastructure and provides isolation, with each request executing in a secure, ephemeral environment. Syntora would configure AWS Identity and Access Management (IAM) roles to enforce least-privilege permissions, ensuring the AI system accesses only the necessary resources. Performance benchmarks would be established during development to meet your operational requirements.
For ongoing security, we would integrate automated dependency scanning into the development and deployment pipeline, typically checking for vulnerabilities daily. Monitoring would be established using services like Amazon CloudWatch to detect unusual activity, such as spikes in failed API calls or unauthorized access attempts to data stores. These alerts would be routed to your designated security team. We would provide cost estimates based on your specific usage patterns and chosen cloud infrastructure during the planning phase.
What Are the Key Benefits?
Deploy Your Compliant System in 4 Weeks
Go from initial CRA gap analysis to a production-ready, privately deployed AI system in 20 business days. Meet your compliance deadlines without a long implementation.
One Fixed Build Cost, Not a SaaS Bill
We scope the work as a single project with a fixed price. After launch, you only pay for minimal AWS hosting, not a recurring per-seat or per-API-call subscription.
You Own the Code and the Infrastructure
You receive the full Python source code in your GitHub repository and the system runs in your AWS account. You have total control and ownership of your AI security governance.
Automated Security Monitoring Built In
We configure CloudWatch alarms and automated vulnerability scanning from day one. You get alerts on potential issues without needing a dedicated security team to watch logs.
Connects to Your Production Databases
Because the system runs in your private cloud, it can securely connect to your existing Postgres or MySQL databases. No need to expose your data to a third-party vendor.
What Does the Process Look Like?
CRA Gap Analysis (Week 1)
You provide documentation on your AI system's function. We deliver a requirements document that maps your specific use case to the technical controls mandated by the CRA.
System Build & Review (Weeks 2-3)
We build the FastAPI application and set up the Supabase logging infrastructure. You receive access to the private GitHub repository to review the code as it's written.
Private Deployment (Week 4)
We deploy the system on AWS Lambda within your cloud account. You receive the live API endpoint and a walkthrough of the IAM roles and security group configurations.
Handoff & Support (Week 5+)
We deliver a technical runbook covering monitoring, common issues, and the update process. You get 30 days of included post-launch support for any questions or tuning.
Frequently Asked Questions
- How much does a CRA-ready system cost to build?
- The cost depends on the AI system's CRA risk classification and the number of data sources. A high-risk system requiring extensive logging and third-party assessment is more complex than a low-risk internal tool. We provide a fixed-price quote after a 45-minute discovery call where we review your specific requirements. Book a discovery call at cal.com/syntora/discover to discuss pricing.
- What happens if a vulnerability is found in a dependency?
- Our automated scanning detects new vulnerabilities in open-source packages daily. For critical vulnerabilities, we have a 48-hour service level objective to test, patch, and deploy an update. The deployment is managed through your GitHub repository using CI/CD, so you have a full audit trail of the fix. This process is documented in the runbook you receive.
- How is this different from buying a 'CRA-compliant' SaaS tool?
- With a SaaS tool, you inherit their security posture and rely on their audit. With a custom system from Syntora, you have your own dedicated infrastructure. An auditor can inspect your AWS account, your IAM policies, and your immutable logs directly. This provides a much higher level of assurance and simplifies the conformity assessment process because you control all the evidence.
- What does the audit trail actually look like?
- Every event generates a structured JSON log in a Supabase table. This log includes a unique event ID, a timestamp, the user or service principal responsible, the action performed, the model version used for a decision, and the outcome. This format is easily queryable, allowing you to generate reports for auditors in seconds by running a simple SQL query against the log table.
- Do we need an internal security team to manage this?
- No. The system is designed for a small engineering team to manage. The automated monitoring and alerting handle 99% of events. The runbook we provide details the specific steps for the most common manual tasks, such as granting a new developer access or investigating a CloudWatch alarm. Syntora also offers a monthly retainer for ongoing management.
- What if the EU updates the CRA requirements after you build this?
- Because the system is built with standard Python and FastAPI, it is straightforward to modify. Changes to logging requirements or security controls can be scoped as a small, fixed-price project. You are not locked into a proprietary platform. You own the code, so any competent Python developer can make the required updates without needing to learn a specialized tool.
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