Our capabilities
Services
Five practice areas, delivered by senior practitioners. Cloud, on-premises, and hybrid environments.
AI strategy and readiness
Decide where AI belongs before you build
Most AI programs stall because the use case was selected before anyone measured the value or the risk. We evaluate the portfolio of candidate use cases, score them on business impact and feasibility, and produce a sequenced roadmap with cost models and success criteria. The output is a decision document an executive team can fund.
- Use case discovery, scoring, and prioritization
- AI readiness assessment across data, security, and operations
- Build, buy, and partner evaluation
- Cost modeling and unit economics for model usage
- AI governance, acceptable use, and policy design
OpenAI solution architecture
Reference architectures built on the OpenAI platform
We design and oversee delivery of production systems on the OpenAI platform: retrieval-augmented generation over enterprise content, structured extraction from documents, agentic workflows with tool calling and human approval gates, and evaluation harnesses that measure quality before and after release. Architecture decisions are documented, reversible, and matched to the workload rather than the trend.
- Retrieval-augmented generation and enterprise search
- Structured output, function calling, and tool integration
- Agentic workflow design with human-in-the-loop controls
- Evaluation, benchmarking, and regression testing
- Model selection, routing, caching, and cost control
Product availability, technical capabilities, and licensing requirements vary. Recommendations are validated against current product documentation during each engagement.
Cybersecurity and executive advisory
Virtual CISO and CTO leadership, on demand
Strategic security and technology leadership for organizations that need senior guidance without a full-time hire. We develop security roadmaps, manage vendor and risk posture, engage with boards and auditors, and serve as the technology voice in executive decisions. AI systems are treated as in-scope assets, not exceptions, with controls for prompt injection, data exposure, and model supply chain risk.
- Fractional, project-based, or interim security and technology leadership
- Security program design against NIST CSF 2.0, CIS Controls v8, and ISO 27001
- AI-specific threat modeling and control design
- Third-party and model supply chain risk review
- Board, audit, and regulator engagement
Data and infrastructure
The foundation AI systems depend on
AI quality is bounded by data quality, access control, and platform reliability. We design data architecture, retrieval pipelines, identity and access models, and the network and cloud foundations underneath them. Work spans Microsoft Fabric and Power BI, Azure and multi-cloud estates, on-premises systems, and hybrid environments with regulated data.
- Data architecture, pipelines, and retrieval readiness
- Microsoft Fabric, Power BI, and Azure platform design
- Identity, access management, and data classification
- Network architecture, backup, and disaster recovery
- Cloud, on-premises, and hybrid integration
IT operations
Mature operations without enterprise overhead
We help IT teams move from reactive firefighting to structured operations, then extend that operating model to cover AI systems in production. Engagements include endpoint management, vulnerability remediation programs, service delivery design, vendor management, and the monitoring and escalation paths that keep AI workloads observable and accountable.
- Operating model and service delivery design
- Endpoint management and vulnerability remediation
- Monitoring, logging, and incident escalation for AI workloads
- Vendor and license management
- Knowledge transfer and handoff to internal teams