Our AI Approach

The Freedom Project Ethos

The Freedom Project was founded on a simple principle: technology decisions should be made with clarity, not confusion. In a landscape dominated by vendor narratives, sales-driven roadmaps, and opaque AI systems, we believe organizations deserve tools that work for them—not for someone else's bottom line.

This philosophy extends to how we build our own products. When we created AIM, we made deliberate choices about how AI would be integrated—choices grounded in our values, not just technical convenience.

More Than an AI Wrapper

Many tools today are simply interfaces layered on top of large language models—what the industry calls “AI wrappers.” They take your input, pass it to an AI, and return whatever comes back. The intelligence is borrowed, not built.

AIM is different. At its core, AIM uses a proprietary methodology we call Retrieval-Augmented Optimization (RAO)—a structured approach that retrieves relevant patterns and reference architectures, scores candidate solutions across multiple dimensions, and optimizes recommendations for your specific constraints.

The AI models we use are tools within this framework, not the framework itself. The intelligence is in the methodology—the structured analysis, the scoring dimensions, the constraint normalization, the architectural patterns. The AI helps us execute at scale; it doesn't define what we do.

Provider Independence

Just as we refuse to be tied to technology vendors in our recommendations, we refuse to be locked into any single AI provider. Our architecture is designed for flexibility—we can switch providers, models, or approaches as the field evolves.

This isn't theoretical. We actively evaluate providers based on quality, cost, and alignment with our values. When better options emerge, we can adopt them without rebuilding our entire system.

Ethical Considerations in Our AI Choices

When selecting AI providers, we consider more than just performance benchmarks. We evaluate:

These considerations led us to choose providers who share our commitment to responsible AI development. We believe that how AI is built matters as much as what it can do.

What We Don't Do

Transparency means being clear about boundaries. Here's what AIM does not do with AI:

• ✕We don't train models on your data. Your assessments, architectures, and business information are never used to train AI models—ours or anyone else's.
• ✕We don't make black-box decisions. Every recommendation AIM provides is grounded in structured analysis. We can explain why a recommendation was made, not just what it is.
• ✕We don't let AI make final decisions. AI assists analysis and generates insights, but human judgment remains central. AIM is a tool for decision-makers, not a replacement.
• ✕We don't hide behind AI limitations. When AI has limitations or uncertainties, we surface them. You'll know what's confident analysis and what requires human validation.