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Advisory Playbook · Austin

Fractional CTO to Ship production AI & modern cloud capabilities in Austin

Move from fragile AI demos to defensible margin.

Customers and boards expect real AI workflows, but naive LLM wrappers risk hallucinations, GDPR/SOC 2 violations, and runaway inference costs.

Principal CTO Execution Blueprint

We design enterprise-safe RAG pipelines, agentic tool-use guardrails, automated eval suites, and tiered model routing tailored to your domain data.

Production-Grade AI & Agentic Architecture for Austin Teams

Every board and founder in Austin wants AI leverage—yet bolting raw consumer LLM prompts onto company data creates hallucinations, runaway token bills, and severe SOC 2 Type II, HIPAA, PCI-DSS, and CCPA/GDPR enterprise controls exposure.

How We Engineer Defensible, High-ROI AI Systems

  • Zero-Retention Private Cloud Boundaries: Deploying via AWS Bedrock, Azure OpenAI, or Vertex AI VPC endpoints so proprietary customer and company data never trains public models.
  • Permissioned RAG & Deterministic Tool-Use: Enforcing row/document-level ACLs, structured JSON schema validation, citation grounding, and human-in-the-loop approval thresholds.
  • Automated Evaluation & Cost Guardrails: Golden-dataset accuracy regression tests on every prompt/model change plus tiered small-vs-frontier model routing.
Representative Execution Pattern

Austin B2B Software & Operations Team

Challenge:Prototype AI copilot suffered from 22% hallucinated citations, slow 14-second responses, and failed enterprise security questionnaires on data residency.
CTO Intervention:Re-architected into a zero-retention VPC RAG pipeline with hybrid lexical/vector retrieval, ACL filtering, streaming responses, and a 250-case automated eval suite.
  • Grounded citation accuracy lifted above 97.5% on production evals
  • Median time-to-first-token reduced under 650ms with 55% lower token cost
  • Approved by enterprise infosec teams across US and UK accounts

Frequently Asked Questions

How do you ensure our Austin company's data is never used to train external AI models?
We strictly architect around enterprise zero-data-retention agreements, VPC-isolated inference endpoints, PII redaction layers, and audit logging compliant with SOC 2 Type II, HIPAA, PCI-DSS, and CCPA/GDPR enterprise controls.

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Pass Investor Tech Checks & Enterprise Security Reviews

Production AI / LLMVC Due Diligence
$4,800 – $9,500 / mo (0% equity)Fractional CTO — Investor & Security Lead
Investor Ready14–21 Days
IP Ownership100% Verified
Equity Taken0%

Likely Architectural Root Cause: Missing system documentation, unchecked security settings, and unanswered compliance forms can stall funding rounds or big customer contracts.

First 14-Day Principal CTO Execution Plan
  • 01Create a clean, investor-ready tech folder (system diagrams, costs, and 12-month roadmap)
  • 02Lock down security, data backups, IP ownership, and SOC 2 / ISO 27001 / GDPR basics
  • 03Join your live investor and enterprise buyer calls directly as your Fractional CTO
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