Secure software development

Unlike traditional nearshore vendors, we add an extra layer of security, privacy, and accountability to every engagement. You should trust Ewents with critical software and sensitive data because:

• We run background checks for every hire before they begin working with client systems or data.
• We carry $5M+ in cyber insurance and E&O coverage to protect our clients in every engagement.
• We sign strict NDAs and IP agreements with every team member before onboarding.
• We can provide secure laptops, configured with security tools such as EDR, DLP, encryption, secure VMs, and other requirements.
• We operate under a well-established Trust and compliance program, available to clients, that explains how we handle business continuity, incident response, backups, access control, privacy, data handling, third-party vendors, and more.
• Our team is certified in AI governance and privacy, having credentials in ISO/IEC 42001, CIPM, and ISO/IEC 27001 to help define AI access, controls, and compliance requirements across engagements.

Beyond secure software development, Ewents also provides dedicated cybersecurity services. Our team can support AI security, SOC operations, fractional CISO services, cloud security, and compliance engineering for regulated industries.

We work with a wide range of security tools and generally integrate them across two main areas. First, on the application security side, our engineers use tools such as Snyk, GitHub Advanced Security, SonarQube, Semgrep, OWASP ZAP, Burp Suite, and Checkov to support dependency scanning, secrets detection, API security testing, Infrastructure-as-Code (IaC) checks, container scanning, and CI/CD security gates before software reaches production. Secondly, once the application is running, we can also integrate Datadog, Splunk, ELK, Sentry, and native security services across AWS, Azure, and GCP for logging, monitoring, alerting, vulnerability detection, cloud security monitoring, and incident response. Beyond these areas, our engineers can establish which risks to address first, how to prioritize vulnerabilities, and how to route alerts to the right team. Across these initiatives, we generally follow the three core principles of the C-I-A triad:

• Confidentiality: Protect sensitive data and limit access to authorized users, applications, and systems.
• Integrity: Preserve the accuracy and trustworthiness of code, data, and systems by preventing unauthorized or unintended changes.
• Availability: Maintain reliable, resilient systems that remain accessible when the business needs them.

To enforce AI agent security, we focus on the two most important aspects: controlling what the agent can access and controlling what it can do. First, we follow the principle of least-privilege access so agents reach only the APIs, data, applications, and systems they need. We avoid giving agents broad or direct access to sensitive environments whenever possible. Afterward, we establish guardrails around what agents can do, enforcing approval steps for higher-risk changes, logging, monitoring, and clear rules on what an agent can read, modify, or execute.

If you’re interested in secure AI application development services, reach out to our team.

Yes. Our team has a lot of experience in legacy code modernization for AI adoption. Based on past engagements, we usually start the discovery stage with a call with the client to do a high-level technical review and security assessment of the environment. During discovery, we review data flows, architecture, dependencies, integrations, access controls, vulnerabilities, and overall security posture. After looking at the findings, we may recommend:

• Refactoring critical components to reduce technical debt and make the application easier to extend or integrate with AI services.
• Cleaning, standardizing, and formatting data so AI agents and models can work with more consistent, reliable, and well-structured information.
• Hardening API security, identity, and access controls so AI agents can interact with systems through secure, well-defined interfaces, including stronger IAM and least-privilege access.
• Improving security tooling and delivery pipelines with SAST, dependency scanning, secrets detection, vulnerability management, automated testing, observability, and stronger CI/CD controls.

Modernizing your systems can be a significant investment, but the long-term return can be much greater. Once your organization has a clean, cloud-based foundation, it becomes easier to deploy AI agents and support new integrations, while drastically reducing ongoing legacy maintenance costs.