Every organization embracing cloud, AI, and modern digital delivery eventually runs into the same question: How do we move fast without creating risk?
The acceleration of AI has widened a trust gap across industries. Boards want innovation. Regulators want assurances. Customers want transparency. And technology leaders are left balancing urgency with responsibility.
In financial services, healthcare, SaaS, and increasingly every data-driven business, the pressure to innovate collides with a growing set of security, privacy, and compliance expectations. In that environment, trust isn’t a soft concept, it’s a strategic requirement.
The New Trust Gap in Modern Transformation
As organizations adopt copilots, build data platforms, and modernize applications, three forces are reshaping how leaders think about security – not just for their own environments, but for every technology partner they rely on:
- The velocity of AI development
Teams can ship faster than ever. If your developer’s security governance can’t keep pace with their delivery, they can inadvertently become the weakest link in your AI and cloud initiatives. - Expanding data surfaces
Cloud-native systems, API-driven architectures, real-time analytics, and distributed apps create more entry points for attackers and more responsibility for defenders. Every partner working inside your architecture becomes part of your attack surface, which means their controls must be as strong as yours. - Heightened expectations from customers and regulators
Financial services institutions need evidence of controls. SaaS companies must protect customer data to win enterprise deals. Healthcare and life sciences organizations face increasing scrutiny around privacy and operational resilience. Your internal systems need to be governed, along with every part of your delivery and development ecosystem.
The result is a growing trust gap between what organizations want to build and what they can confidently deliver. When your own security posture is mature, your ability to confidently deliver AI-enabled transformation depends on the maturity of the partners supporting you.
Why SOC 2 Exists
SOC 2 is a framework created to validate whether a company has the right controls in place to handle customer data safely and responsibly. It’s built on five Trust Service Criteria:
- Security
- Availability
- Processing Integrity
- Confidentiality
- Privacy
Where other certifications focus on infrastructure or specific systems, SOC 2 evaluates how an organization operates: processes, governance, monitoring, incident response, and the cultural commitment behind them. SOC 2 is about demonstrating trustworthy behavior. To achieve SOC 2 certification, an organization works with an independent auditor to verify these controls and behaviors are in place.
What SOC 2 Means for Lantern
For our team, achieving SOC 2 certification means that our systems, processes, and delivery methods have been independently validated. Customers gain assurance that their data, and the data we work with on their behalf, is handled with rigor. From AI copilots to app modernization to data platforms, every Lantern engagement is supported by verified operational controls. Our Trust Center provides real-time visibility into our policies, controls, and compliance posture. This is part of a long-term commitment to build trust deliberately and make it measurable.
As the AI landscape evolves, we know that trust is a competitive edge that separates high-performing organizations from those that fall behind.
SOC 2 reinforces Lantern’s commitment to responsible, transparent, and resilient delivery so our customers can move faster with confidence.
SOC 2 is a part of a continuous journey toward higher standards of operational excellence, tighter alignment with our customers’ regulatory expectations, and deeper investment into secure AI and cloud capabilities.
If your organization is preparing for AI adoption, cloud modernization, or application transformation – and trust is an essential part of that journey – we’re here to help.
