At a Glance
Overview
Valere partnered with Onyx AI to execute a complete digital transformation—migrating their AI-powered licensing advisory chatbot from a constraint-heavy Zapier platform to a scalable, enterprise-grade AWS cloud infrastructure. This case study demonstrates how strategic cloud migration combined with AI-native development enables SaaS companies to break through market barriers and capture enterprise opportunities.
The Challenge
Onyx AI had developed an innovative solution helping Microsoft partners navigate complex licensing decisions, but their Zapier-based architecture created insurmountable barriers. Scalability constraints prevented handling enterprise loads, limited AI customization reduced accuracy, integration restrictions blocked advanced features, and inconsistent performance plagued peak periods. They couldn’t target enterprise customers, faced high recurring costs without scalability benefits, and lacked credibility with buyers requiring robust infrastructure—losing competitive advantage in the $25 billion Microsoft CSP opportunity.
Beyond infrastructure, they faced critical AI accuracy challenges: inconsistent response quality, variable confidence in recommendations, unpredictable conversational tone, and edge cases requiring refinement. They needed enterprise-grade AWS infrastructure, scalable architecture for AI workloads, advanced prompt engineering, complete UX/UI redesign, and a partnership willing to iterate until achieving production-quality outputs.
Solution Implemented
Valere delivered a complete platform transformation combining AWS cloud expertise with AI-native development capabilities to rebuild Onyx AI’s solution from the ground up. The comprehensive engagement included custom backend infrastructure on AWS with scalable API development, database migration and optimization, and load testing for performance tuning.
Valere implemented iterative prompt engineering cycles, LLM fine-tuning for domain expertise, output validation and quality assurance, and response accuracy improvement methodology. The team executed a complete interface redesign with user experience optimization, enterprise-grade design standards, and accessibility enhancements.
The solution integrated Microsoft licensing data with comprehensive quality assurance, security and compliance validation, and complete documentation and knowledge transfer, prioritizing scalability for enterprise customer loads while maintaining production-quality AI outputs.
About the Company
Onyx AI provides AI-powered, expert-backed licensing advisory solutions that help Microsoft partners and Cloud Solution Providers navigate complex licensing decisions and capture commercial opportunities. The platform addresses a $25 billion market opportunity, helping CSPs reduce support overhead and maximize revenue from Microsoft partnerships through their CSP Growth Engine—an AI-powered chatbot delivering instant, accurate Microsoft licensing guidance based on expert knowledge and real-time data.
Chris Brown (CEO) leads the company with clear vision for modernizing partner success in the Microsoft ecosystem. His commitment to understanding the specific needs of CSPs and their customers was evident throughout the engagement, driving the platform’s evolution from prototype to enterprise-grade solution capable of serving customers with $100M+ in annual revenue.
The Challenge of Achieving Enterprise Credibility
When Onyx AI approached Valere, their platform had hit a ceiling. The Zapier-based architecture that enabled rapid prototyping had become their biggest limitation, creating insurmountable barriers to enterprise growth.
Scalability Crisis
Zapier workflows couldn’t handle enterprise customer loads, with performance degradation during peak usage and no auto-scaling capabilities for variable AI workloads. The infrastructure simply wasn’t designed for production AI inference at scale.
AI Quality and Customization Constraints
The platform had limited ability to implement advanced prompt engineering or infrastructure for iterative model refinement. Constrained by Zapier’s generic AI integrations, Onyx AI couldn’t achieve the production-quality accuracy requirements that enterprise customers demanded. Early iterations produced inconsistent response quality across use cases, variable confidence levels in licensing recommendations, and unpredictable conversational tone that undermined user trust.
Integration and Development Restrictions
The team was unable to build custom APIs for specialized features, had limited data processing capabilities, and faced restricted access to Microsoft licensing data. There was no flexibility for the complex AI workflows needed to serve sophisticated enterprise use cases.
Cost Structure Without Benefits
Fixed Zapier subscription costs at scale meant paying for capabilities they couldn’t use, with no cost optimization for actual usage patterns. The recurring fees provided no scalability benefits, creating an unsustainable economic model.
Business Impact: Market Positioning Crisis
Enterprise customers with $100M+ revenue required robust infrastructure that Zapier couldn’t provide, creating competitive disadvantage against solutions with production-grade platforms. This credibility gap prevented conversations with target market segments and limited revenue potential due to addressable market constraints. Professional CSPs needed a platform they could trust for licensing decisions worth millions of dollars annually.
The GenAI Development Challenge
Beyond technical infrastructure, Onyx AI faced challenges inherent to AI-native development: subjective quality requirements around conversational tone and response confidence, unpredictable GenAI behavior requiring extensive testing, iterative refinement needs that generic platforms couldn’t support, and the gap between demo-quality outputs and production-quality standards that enterprise buyers expected.
The Partnership Approach
Chris Brown, CEO of Onyx AI, selected Valere to transform Onyx AI’s platform into an enterprise-grade solution after evaluating multiple AI/ML development firms. Several factors distinguished Valere during the selection process:
- Proven AI Competency Beyond Buzzwords: Valere demonstrated deep understanding of LLM fine-tuning, prompt engineering challenges, and enterprise deployment requirements.
“Their AI capabilities weren’t theoretical—they demonstrated deep understanding of LLM fine-tuning, prompt engineering challenges, and enterprise deployment requirements.”
— Chris Brown, CEO, Onyx AI
- Honest Assessment of AI Development Complexity: Rather than overselling GenAI capabilities, Valere provided realistic expectations about AI development complexity, timelines, and the iterative refinement required to achieve production-quality outputs. The team was transparent about trade-offs and honest about what could be achieved within specific timeframes.
- Commitment to Quality Over Scope: Valere demonstrated willingness to iterate beyond initial scope to meet quality standards. The team treated Onyx AI’s success metrics as their own, with leadership remaining engaged throughout the project lifecycle rather than delegating to junior team members after contracts were signed.
- Strategic Partnership, Not Just Implementation: Valere operated as an extension of the Onyx AI team rather than an outside vendor. The team challenged assumptions productively, provided guidance on enterprise positioning, and advised on technical architecture decisions that would impact long-term scalability.
As Chris Brown noted, “The leadership team inspired confidence. They understood that getting AI right for enterprise customers required more than technical competence—it required partnership, iteration, and commitment to excellence.“
The Solution
Valere engineered a complete platform transformation combining AWS cloud expertise with AI-native development methodology to rebuild Onyx AI’s solution from the ground up. Rather than simply migrating the existing Zapier workflows, Valere redesigned the entire architecture to enable enterprise-grade AI capabilities while building on a foundation that could scale with Onyx AI’s growth.
Strategic AWS Infrastructure Architecture
Valere architected a scalable, secure, and high-performance AWS infrastructure purpose-built for AI-native applications. The cloud platform design included serverless compute with AWS Lambda for auto-scaling AI inference loads, custom API development through AWS API Gateway for enterprise integrations, optimized data layer with AWS RDS and S3 for transactional data and document storage, and production-grade security controls with encryption, IAM policies, and compliance readiness. The architecture enabled cost efficiency through pay-as-you-go models, performance consistency under variable loads, and future-proof foundation for additional AI features.
Iterative AI Model Refinement (Most Complex Challenge)
The AI optimization process became the most technically demanding aspect of the engagement. Valere implemented a continuous improvement methodology featuring iterative prompt engineering cycles, LLM fine-tuning for Microsoft licensing domain expertise, comprehensive output validation and quality assurance testing, and response accuracy improvement through real-world scenario testing. The team deployed prompt engineering changes, tested with actual use cases, measured accuracy and user satisfaction, identified edge cases and quality gaps, refined prompts and validation logic, and repeated until production quality was achieved. This iterative approach addressed the inherent unpredictability of GenAI behavior and subjective quality requirements that evolved through testing.
Enterprise UX/UI Transformation
The interface was completely redesigned to meet enterprise-grade design standards with user experience optimization for professional CSPs, responsive design across devices, accessibility enhancements, and performance optimization. The new design reflected the credibility and sophistication that enterprise customers with $100M+ revenue expected from mission-critical business software.
Phased Implementation Approach
Valere executed a comprehensive transformation spanning discovery and technical assessment, AWS architecture design and infrastructure provisioning, backend API development with Microsoft licensing data integration, frontend implementation with enterprise interface, iterative AI refinement cycles extending beyond initial scope, comprehensive load testing and security validation, and phased production deployment with go-live support. The engagement model emphasized transparency about timeline adjustments required for AI quality refinement, with weekly meetings focused on discussing features, testing results, and success criteria.
Post-Launch Optimization Partnership
Even after successful launch, Valere continued partnering with Onyx AI to refine AI outputs based on real-world customer feedback. Activities included real-world edge case identification, prompt engineering micro-optimizations, user experience refinements, and performance tuning based on usage patterns.
“What impressed me most was their willingness to iterate beyond the initial scope when our subjective quality requirements kept evolving. They treated our success metrics as their own and didn’t declare victory until we were confident in the product.“
— Chris Brown, CEO, Onyx AI
The Results
The AWS migration and AI-native development partnership delivered transformational results that fundamentally repositioned Onyx AI for enterprise growth. The platform evolved from a Zapier-constrained prototype into a production-grade solution that enterprise customers with $100M+ revenue could confidently deploy for mission-critical licensing decisions.
Key Outcomes
AI Performance & User Experience Transformation
- 50% improvement in chatbot response accuracy through enhanced prompt engineering framework and iterative model refinement methodology
- 30% increase in user satisfaction scores driven by enterprise-grade user experience, improved conversational tone, and consistent response quality
- Production-quality outputs replacing demo-quality prototypes, with edge cases handled effectively and ongoing refinement capability established
- Faster response times enabled by optimized AWS infrastructure and serverless architecture
Enterprise Market Positioning Success
- Unlocked $100M+ revenue customer segment previously inaccessible due to infrastructure limitations
- Infrastructure credibility established with enterprise buyers requiring robust, scalable platforms
- Security and compliance standards met, enabling conversations with sophisticated procurement teams
- Competitive advantage achieved through production-grade platform in $25 billion Microsoft CSP market opportunity
Operational Efficiency & Scalability
- Eliminated recurring Zapier subscription costs through pay-as-you-go AWS model optimized for actual usage patterns
- 40% efficiency gain in feature implementation enabled by flexible AWS architecture and custom API infrastructure
- Auto-scaling capabilities for variable AI workloads ensuring consistent performance during peak usage
- 99.9%+ uptime reliability providing enterprise-grade availability standards
Strategic Business Impact
Market Position Transformation
Before the AWS migration, Onyx AI was limited to small-to-mid market customers with an infrastructure credibility gap preventing enterprise conversations. After the transformation, the company is actively targeting enterprise customers, confidently discussing infrastructure capabilities in sales conversations, and positioned as an innovator in the Microsoft partner ecosystem with CSP Growth Engine featured in IT Channel Oxygen press coverage.
Revenue Growth Foundation
The platform transformation positioned Onyx AI to capture share of the $25 billion Microsoft CSP market with enterprise segments now addressable, higher customer lifetime value potential, and scalable infrastructure supporting aggressive growth plans without technical constraints.
Client Perspective
“Valere’s AI capabilities are the real deal. Many firms claim generative AI expertise, but Valere’s team has demonstrated actual competency in prompt engineering, output validation, and iterative model refinement. The team doesn’t oversell what AI can do and is honest about the work required to achieve production quality.”
“Valere was the right partner for our AI transformation. They have genuine expertise, stay committed through complexity, and deliver enterprise-grade results. If you’re serious about building production AI solutions—not just demos—they’re worth a conversation.”
— Chris Brown, CEO, Onyx AI
Check the full client review on Peerspot.
Conclusion
Onyx AI’s partnership with Valere demonstrates the transformative impact of strategic AWS cloud migration combined with AI-native development expertise for enterprise SaaS companies. The platform evolved from Zapier-constrained prototype to production-grade solution trusted by enterprise customers managing millions in Microsoft licensing decisions.
The combination of scalable AWS infrastructure, iterative AI refinement methodology, enterprise-grade UX/UI design, and genuine partnership commitment created a sustainable competitive advantage in the $25 billion Microsoft CSP market. The 50% accuracy improvement, 30% user satisfaction increase, and unlocked enterprise customer segment validate that production AI requires more than generic tools—it demands specialized expertise, willingness to iterate beyond initial scope, and infrastructure purpose-built for AI workloads.
Looking forward, Onyx AI is positioned to capture significant market share with enterprise-grade infrastructure providing the foundation for continuous AI improvement and advanced feature development that was previously impossible under platform constraints.
