AI hype often outpaces real results, especially for mid-market companies, because standalone models fall short. The key to success is a system-based approach. Read on to learn how to build custom AI solutions that return on investment.
A Systems-Based Approach to AI
In the world of artificial intelligence (AI), there is a persistent gap between excitement and real-world application. Large language models and flashy generative AI tools dominate headlines as businesses struggle to translate this hype into meaningful outcomes. For mid-market companies, this challenge is particularly acute. Yet, there exists a transformative opportunity for these organizations to leap ahead — if they adopt a strategic, systems-based approach to AI.
This is our unique approach at Rotational Labs, where we specialize in creating tailored compound AI systems designed to address unique organizational challenges and delivering business impacts that cannot be achieved with standalone models. In this piece, we’ll describe the advantages of Rotational Labs’ approach and explain how mid-market companies can leverage these proven strategies. By the end, you’ll understand why starting with an AI readiness assessment by Rotational Labs is the best way to future-proof your business and seize AI’s transformative potential.
The Hype vs Reality of AI
The Current Landscape
Artificial intelligence has captured the imagination of industries worldwide, yet many projects fail to deliver tangible outcomes. Large-scale models such as ChatGPT and Google’s Gemini generate buzz, but businesses often find themselves disappointed when these tools cannot navigate real-world complexities. Research has shown that while these models are powerful, their performance in practical applications often depends on how well they integrate into existing systems and workflows.
The Pitfalls of Model-Centric Thinking
A major reason for these failures lies in an overemphasis on the AI model itself, rather than the broader system it operates within. A standalone AI model, no matter how advanced, cannot function effectively without proper integration into a tailored infrastructure. It’s like designing an F1 race car and obsessing over the engine while ignoring aerodynamics, driver controls, and fuel efficiency.
Rotational Labs recognizes this flaw and approaches AI adoption with a focus on compound systems. These systems bring together models, heuristics, and human-in-the-loop interfaces to create reliable, scalable solutions that deliver measurable outcomes for businesses.
The Rotational Labs Approach
Endeavor Platform: A Tailored Solution
At the heart of Rotational Labs’ strategy lies our proprietary Endeavor platform. Endeavor is not an off-the-shelf software product but a dynamic framework our AI systems engineers use to coordinate and manage AI lifecycles. Each implementation of Endeavor is custom-built to suit the specific needs of the client, ensuring that all AI components work seamlessly together.³
Key features of Endeavor include:
- Model-Agnostic Flexibility: Compatible with diverse business environments and cloud providers.
- Built-in Governance: Ensures accountability, compliance, and trust in AI operations.
- Automated Lifecycle Management: Streamlines deployment, monitoring, and adaptation of AI systems
Proven Success Across Industries
We know this approach works and have validated it for customers in many sectors including finance, cybersecurity, and supply chain management. For instance, our solutions have:
- Reduced manual analyst tasks by 90% in supply chain analytics.
- Enabled AI-driven fraud detection in financial services, cutting oversight costs by 30%.
These examples highlight the versatility and impact of Rotational Labs’ compound systems.
Why Compound Systems Beat Standalone Models
Model Agility and Adaptability
In complex business environments, agility is crucial. Compound systems, like those developed by Rotational Labs, allow businesses to swap or update individual AI components without overhauling the entire architecture. For example, Rotational’s work on a risk model for a major client ensures that evolving algorithms do not disrupt other system components.
Cost Efficiency and ROI
Standalone AI tools often incur high costs due to inefficiencies in scaling and integration. Compound systems, by contrast, maximize cost-efficiency by optimizing every layer of the solution—from data pipelines to model deployment. Rotational Labs’ emphasis on building tailored, high-performing systems has consistently delivered measurable ROI, including reduced downtime and faster time-to-insight.
The Opportunity for Mid-Market Companies
Unique Challenges and Opportunities
For mid-market companies, adopting AI can seem daunting. Many lack the in-house expertise or budget to experiment with advanced AI tools. However, the risks of inaction are growing. Competitors who embrace AI today will gain significant advantages in operational efficiency, customer engagement, and product innovation.
Rotational Labs’ Value Proposition
Rotational Labs excels at meeting organizations where they are, regardless of their AI maturity. Through their AI readiness assessments, they help companies:
- Identify high-impact opportunities tailored to their business needs.
- Develop actionable strategies that align with their goals.
- Build scalable, sustainable AI solutions
The Call to Action
Why Start Now?
The best time to adopt AI was yesterday; the next best time is today. Early adopters not only gain a competitive edge but also build critical internal expertise that compounds over time. By focusing on practical, high-impact use cases, mid-market companies can start small and scale as they gain confidence in their AI capabilities.
Partnering with Rotational Labs
Instead of offering one-size-fits-all solutions, Rotational Labs collaborates closely with clients to design bespoke systems that address their unique challenges. An AI readiness assessment is the ideal starting point for any organization looking to explore AI’s potential. This strategic evaluation helps businesses understand where they stand, what’s possible, and how to proceed confidently.
Conclusion
AI is not a luxury but a necessity for mid-market companies aiming to thrive in today’s competitive landscape. By embracing a system-focused approach, businesses can overcome the limitations of standalone models and unlock AI’s full potential. Rotational Labs’ expertise in building tailored compound systems ensures that every client achieves measurable, lasting success.
Don’t wait for the future to leave you behind. Contact Rotational Labs today for an AI readiness assessment, and take the first step toward transforming your business with AI.
Resources
Stanford Webinar - Large Language Models Get the Hype, but Compound Systems Are the Future of AI. Available at: https://youtu.be/vRTcE19M-KE.
Mekala, R.R., Razeghi, Y., & Singh, S. (2024). “EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-context Learning.” arXiv:2309.10687v3.
Sclar, M., Choi, Y., & Tsvetkov, Y. (2024). “Quantifying Language Models’ Sensitivity to Spurious Features in Prompt Design.” arXiv:2310.11324.
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