Building the
Future with AI and Innovation.

Valere's DSLC is a flexible, iterative framework consisting of four core phases: Discovery, UX Design, Build, and Post Launch. This adaptable methodology allows each engagement to receive a customized approach tailored to specific project requirements. The process begins with comprehensive discovery to understand business needs and culminates in ongoing maintenance and support to ensure long-term success.

Valere Velocity delivers rapid prototyping and proof-of-concept development within 2-4 weeks. This accelerated approach focuses on validating core concepts quickly, allowing teams to make informed decisions before committing to full-scale development. The process includes essential discovery work, wireframe creation, and functional prototype development to demonstrate feasibility and gather early feedback.

The Discovery phase involves identifying customer and business needs through stakeholder interviews, user research, and requirements analysis. Our team assesses existing systems, defines user stories, and establishes clear project scope and objectives. Deliverables include low-fidelity wireframes, flow diagrams, and conceptual visuals that provide a foundation for the entire project development cycle.

The Build phase adapts to either Fixed or Retainer models depending on project requirements. Fixed engagements follow predetermined milestones with specific deliverables, while Retainer models provide ongoing development support through dedicated team allocation. Both approaches include continuous testing, quality assurance, and iterative development to ensure functional solutions that meet defined business needs.

The AI Assessment & Planning phase is a 2-3 week consultation designed to define business objectives, establish AI feasibility, and conduct comprehensive stakeholder interviews. This foundational phase delivers a Mini AI Transformation Playbook containing strategic adoption insights and an AI Roadmap Outline detailing phased implementation approaches. The assessment ensures strategic clarity and establishes a strong foundation for impactful AI integration.

Valere specializes in machine learning implementation, natural language processing, computer vision, predictive analytics, and intelligent automation solutions. Our team works with industry-standard frameworks and maintains expertise across cloud-native AI services. We focus on identifying high-value AI applications that drive measurable business outcomes rather than implementing technology for technology's sake.

Our AI transformation follows an agile, iterative process that analyzes organizational readiness and identifies specific areas where AI can deliver maximum value. We begin with feasibility assessments, develop proof-of-concept solutions, and gradually scale successful implementations. This approach minimizes disruption while ensuring sustainable adoption across teams and departments.

The AI Product Manager oversees strategic AI implementation, ensuring solutions align with business objectives and user requirements. This specialized role bridges technical development and business strategy, managing AI-specific considerations like data requirements, model performance, and integration complexity. The AI Product Manager ensures AI solutions deliver practical value while maintaining technical excellence.

The Crew model works best for long-term partnerships requiring ongoing development support, continuous product evolution, or situations where internal technical resources are limited. This objective-based approach provides dedicated team allocation with high flexibility to adapt to changing requirements. It's particularly effective for startups, continuous product development, and post-release support scenarios.

The Fixed Price model provides complete cost predictability with predetermined deliverables and milestone-driven progress. This output-based approach works well for projects with clearly defined scope, minimal expected changes, and strict budget requirements. Clients receive transparent accountability through established milestones and deliverables, making it ideal for specific feature development or well-defined integration projects.

Time & Materials operates as an outcome-based model where billing reflects actual hours worked by team members. This approach provides maximum flexibility for projects with evolving requirements, undefined scope, or need for true staff augmentation. Clients receive transparent monthly billing based on actual work completed, making it suitable for MVP development, ongoing maintenance, and projects requiring iterative feedback.

Valere's flexible approach allows model transitions based on evolving project needs and requirements. Many clients begin with Fixed engagements for initial development phases and transition to Crew or Time & Materials models for ongoing support and feature development. Our team works with you to identify the most appropriate model for each project phase.

Team composition varies by phase and engagement model. Discovery phases include Discovery Leads, UX/UI Designers, and Software Architects. Build phases add Technical Leads, Quality Assurance Engineers, and developers for code development. All projects maintain consistent Project Manager and Account Manager support throughout the engagement lifecycle.

Quality assurance remains consistent across all team locations through standardized processes, continuous integration protocols, and rigorous testing frameworks. Our integrated team structure maintains unified cultural standards and communication protocols regardless of team member location. Regular code reviews, automated testing, and comprehensive documentation ensure consistent quality delivery.

The Technical Lead provides architectural oversight, technology decisions, and development guidance throughout the project lifecycle. This role ensures technical solutions align with business requirements while maintaining scalability, security, and performance standards. Technical Leads coordinate between different development specialists and maintain technical quality across all project deliverables.

Team size varies based on project scope, timeline, and complexity requirements. Smaller projects may involve 3-5 team members, while enterprise implementations can include 10-15 specialists across different domains. Our resource allocation ensures appropriate expertise levels while maintaining efficient communication and project coordination.

Phase duration depends on project complexity and scope. Discovery phases typically require 2-4 weeks, UX Design phases span 3-6 weeks, and Build phases range from 8-20 weeks depending on requirements. AI Assessment & Planning requires 2-3 weeks for comprehensive analysis. We provide detailed timeline estimates during initial project discussions.

Discovery delivers wireframes, flow diagrams, requirements documentation, and project scope definition. UX Design produces interactive prototypes, design systems, and style guides. Build phases deliver functional applications, comprehensive testing results, and deployment-ready code. Post Launch includes maintenance documentation, performance monitoring, and enhancement recommendations.

Progress tracking adapts to engagement model requirements. Fixed projects follow predetermined milestone schedules with specific deliverable checkpoints. Retainer engagements use agile sprint methodologies with regular reviews and iterative delivery. All projects include consistent communication protocols and transparent progress reporting throughout development cycles.

Requirement changes are managed differently across engagement models. Fixed engagements require formal change orders for scope modifications. Retainer and Time & Materials models accommodate changes through agile methodologies and iterative planning. Our team works collaboratively to assess change impacts and adjust project approaches accordingly.

Post-launch support includes security patches, incremental updates, performance monitoring, and feature enhancements. Valere offers flexible maintenance agreements ranging from basic bug fixes and security updates to comprehensive ongoing development support. Support levels can be customized based on application complexity and business requirements.

Scaling support includes performance monitoring, infrastructure optimization, and feature enhancement development. Our team analyzes usage patterns, identifies optimization opportunities, and implements improvements to handle increased demand. We provide both technical scaling solutions and strategic guidance for business growth requirements.

Comprehensive documentation includes technical specifications, deployment guides, user manuals, and maintenance procedures. For AI implementations, documentation covers model performance metrics, data requirements, and monitoring protocols. All documentation supports knowledge transfer and enables internal team management of delivered solutions.

Knowledge transfer and training support helps internal teams understand and maintain delivered solutions. Training covers technical implementation details, best practices, and ongoing maintenance requirements. For AI solutions, training includes model management, performance monitoring, and strategic optimization approaches.