Technology decisions made under pressure tend to create the debt that slows you down for years. We give you an independent, security-informed perspective — so your stack choices are defensible, your AI use is safe, and your platform can evolve without a rewrite.

No vendor allegiances. No preferred resellers. Just clear recommendations with trade-offs explained.

What we help you decide

Architecture Fit

  • Is your current stack fit for purpose?
  • What to keep, replace, or phase out
  • Avoiding lock-in and reducing technical debt
  • Monolith vs services vs serverless trade-offs

AI Platform Choices

  • Managed provider vs self-hosted models
  • Data residency, latency, and cost analysis
  • Model selection for your use case and risk profile
  • Fine-tuning and RAG pipeline architecture

AI Safety & Privacy

  • Prompt and response controls (input/output filtering)
  • PII handling in prompts, completions, and embeddings
  • Red-teaming and abuse scenario analysis
  • Model guardrails and content policy design

Core Platform Picks

  • API gateways and WAF selection
  • Identity: SSO, MFA, and authentication providers
  • Secrets management and vault strategy
  • Observability, logging, and alerting stack

Engagement models

Deliverables

DeliverableWhat you get
Decision BriefOne-pager per choice with trade-offs, costs, and risk
Architecture SketchAnnotated diagram of target state with migration notes
Hardened BaselinesIaC and policy snippets where applicable
Operational RunbookRisks, limits, and how to scale each component
Debrief Call30-minute walkthrough and Q&A

When this helps

  • Evaluating AI platforms — choosing between OpenAI, Anthropic, Azure AI, self-hosted, or hybrid
  • Pre-fundraise or pre-acquisition — technology due diligence preparation
  • Platform migration — moving cloud providers, replacing auth stack, or adopting Kubernetes
  • Compliance groundwork — EU AI Act, ISO 42001, or AI-specific SOC 2 addendum readiness