At Thala, we build the cognitive layer between your data and your decisions
helping small businesses make smarter decisions with AI-driven dashboards and memory systems
The Cognitive Gap We Bridge
Most businesses drown in data while starving for insight
Our Approach
This is why our Thalamic Business Intelligence™ approach works differently. We create the cognitive layer between your data and your decisions
Adaptive Intelligence Dashboards
Context-aware dashboards that surface different insights based on your recent meetings and current priorities—not static reports, but living decision support that knows what matters now.
Contextual AI Memory Systems
Custom memory architectures for your AI agents that learn from your processes, retain relevant context, and surface insights when they're actually needed—keeping your team focused instead of overwhelmed.
Process-Native AI Integration
AI tools built around your existing workflows and compliance requirements, not generic chat interfaces—making adoption natural and keeping regulated businesses secure.
Capability Transfer & Ownership
We build your internal AI leadership capacity, training someone on your team to own and evolve these systems—sustainable transformation, not vendor dependency.
Why Most AI Fails (And How We Avoid It)
The statistics are sobering: 70-80% of AI initiatives fail to deliver meaningful business value12, with some studies suggesting rates as high as 95%16. But these failures follow predictable patterns—and our Thalamic Business Intelligence™ approach is specifically designed to avoid them.
Strategic, Not Technical Failures
The primary failure mode isn't technical—it's strategic. Organizations fall in love with impressive AI capabilities instead of solving real business problems. Research shows that 70% of implementation challenges stem from people and processes, not algorithms3.
Culture-First Preparation
We've learned that successful AI integration starts with cultural preparation. Many teams need to develop experimental mindsets and positive-sum thinking before new tools feel like opportunities rather than threats.
Data Chaos Kills AI
85% of AI projects fail because of data quality4. But the real problem is deeper: scattered information across platforms, fragmented context, and systems drowning in irrelevant data. Most organizations feed their AI everything and hope it figures out what matters.
Data Intelligence First
Our systems succeed because we solve the data intelligence problem first. Like the thalamus filtering sensory input to surface what deserves attention, our approach organizes and contextualizes your data before your AI agents ever see it.
We don't build AI projects. We build decision intelligence systems that happen to integrate AI.
About Dave Beck (founder, lead architect)
I spent my twenties and early thirties building what looked like the perfect academic life—PhD, co-founding degree programs, meaningful research. Then I realized my kids would only be young once. Seven years sailing Caribbean waters with my family taught me that the most valuable skill isn't processing information faster, but choosing what deserves your attention in the first place.
That insight shapes everything I build. Over 18+ years, I've worked from university research labs to startup technical leadership, always focusing on systems that help people make better decisions with less noise.
My technical work spans LangChain for agent orchestration, TensorFlow for custom ML models, and NextJS/tRPC/Cube for business dashboards—but the real value is in designing systems that know what matters when.
I architect every system for eventual ownership transfer, with comprehensive documentation that lets your team take control and evolve these capabilities independently.
Who We Work With
Innovation-focused SMBs (5-200 employees)
We specialize in businesses navigating classic growth transitions—moving from founder-led to team decision-making, bringing in outside talent, or planning for key retirements. These businesses understand that better decision-making infrastructure is their competitive edge.
Our clients typically have a history of technical R&D or early technology adoption. They've tried the "hot" SaaS solutions, but found themselves context-switching between platforms and molding their working practices to fit the functionality instead of the other way around.
Many operate in regulated environments where compliance matters: healthtech, financial services, fintech, and businesses handling personal data under GDPR, PIPEDA, or CPRA. For these companies, scattered data across platforms and shadow AI usage isn't just inefficient—it's a risk they can't afford.