Pesdoe

FAQs

Frequently Asked Questions

What makes Pesdoe different from other AI consulting firms?

We don’t just create impressive demos, we build production-ready AI systems that work in your real business environment. Our focus on North American compliance requirements (HIPAA, PCI, SOX, NERC/CIP, FedRAMP) means you get AI that meets your regulatory standards from day one, not as an afterthought.

We specialize in regulated industries across North America: Healthcare & Life Sciences, Financial Services & Banking, Manufacturing & Industrial, Retail & E-commerce, Energy & Utilities, and Government & Public Sector. Each industry has specific compliance requirements that we build into our AI solutions.

Our pilot projects typically run 4-8 weeks, depending on scope and complexity. Full implementations vary by service: AI Strategy & Roadmaps take 6-12 weeks, Custom AI Development ranges from 8-16 weeks, and MLOps implementations typically require 4-8 weeks after initial development.

That’s exactly why we created our AI Strategy & Roadmap service. We start with an AI Opportunity Assessment to identify high-value use cases, then conduct Data Readiness Audits to ensure your infrastructure can support them. You get a prioritized roadmap with clear ROI projections and implementation timelines, perfect for board reporting.

Every strategy includes Use-Case Prioritization & ROI Modeling with quantified business impact projections. We don’t just estimate we build measurement frameworks that track actual performance against predicted outcomes. Our clients typically see ROI within 6-12 months of implementation.

Absolutely. Our Custom AI Development service includes API and System Integration as standard practice. We’ve built AI solutions that work with major enterprise systems ERP, CRM, data warehouses, and legacy applications. The key is designing with integration in mind from the beginning.

Prototypes prove concepts; production systems serve customers. Our Custom AI Development delivers production-ready features with proper security, scalability, monitoring, and compliance built-in. We can start with AI Prototyping & MVPs for validation, then scale to full production with proper architecture.

Yes, but you’ll need proper data integration first. Our Data Engineering & Integration service creates unified data pipelines that connect all your sources, cloud and on-premise systems, APIs, databases, and files. We build the data foundation that makes AI possible.

Data Governance and Security is built into every pipeline we create. We implement encryption at rest and in transit, access controls, audit trails, and compliance monitoring that meets your regulatory requirements, HIPAA, PCI, SOX, or FedRAMP standards.

This is exactly what MLOps & AI Operations solves. Production AI needs Model Monitoring and Drift Detection, Automated Retraining and Versioning, and CI/CD for Machine Learning. We build systems that maintain performance and adapt to changing data automatically.

Through continuous monitoring and automated response systems. Our MLOps implementations include drift detection that alerts when model performance changes, automated retraining pipelines that update models with fresh data, and rollback capabilities if new versions underperform.

Our AI Audit & Optimization service is designed exactly for this situation. We conduct Model Accuracy Audits, Data Quality Analysis, and ROI Cost-Benefit Evaluation to identify what’s not working and why. Most audits reveal quick wins that improve performance 20-40%.

AI audits typically cost 10-20% of your original AI investment but often deliver 2-5x ROI improvement. We provide Strategic Recommendations with quantified impact projections, so you can prioritize optimizations by expected return.

AI-powered marketing personalizes experiences at scale and predicts what will work before you spend budget. Our AI-Driven Marketing & Growth service includes Predictive Customer Analytics, automated content optimization, and real-time campaign adjustment that traditional methods can’t match.

Absolutely. We’ve built AI marketing systems for B2B companies that improve lead scoring accuracy by 60-80%, personalize content for decision-makers, and optimize sales funnel conversion. B2B buying cycles are complex AI helps navigate that complexity.

Investment varies by scope and industry requirements. AI Readiness Assessments start at $25k, pilot projects range from $50-150k, and full implementations typically require $150k-500k depending on complexity. We always provide ROI projections that justify investment.

Yes, for well-defined scopes. Our AI Strategy & Roadmap and AI Audit & Optimization services are typically fixed-price. Custom AI Development may be fixed-price after requirements are finalized, or time-and-materials for evolving requirements.

Security and compliance are embedded in every project. We map controls to HIPAA, PCI, SOX, NERC/CIP, and FedRAMP requirements as appropriate. All model, data, and infrastructure decisions are documented for auditability and scale. We never handle data in ways that violate your compliance requirements.

Yes. We build FedRAMP-ready solutions using authorized cloud infrastructure (AWS GovCloud, Azure Government, Google Cloud for Government) and implement the 400+ security controls required for FedRAMP High authorization when needed for government clients.

Most clients begin with either an AI Readiness Assessment to understand their current state or a Strategy Call to discuss specific challenges. Both options help us recommend the right starting point for your situation and objectives.

We work with organizations at different stages. Startups typically start with AI Prototyping & MVPs or focused Custom AI Development. Enterprises usually begin with AI Strategy & Roadmap or AI Audit & Optimization. SMBs often benefit most from AI-Driven Marketing & Growth services.

Timeline depends on the service. AI Strategy & Roadmap delivers actionable plans in 6-12 weeks. Custom AI prototypes can be working in 4-6 weeks. Production systems typically require 8-16 weeks. MLOps implementations show performance improvements within 2-4 weeks of deployment.