AI Engineering
Reliable and Reproducible.
I turn language models into measurable business processes - quality, cost, and latency under control. Consulting for companies that demand command over their data and outcomes.
The challenge
RAG system with 3.2s (P95) and cost/query +40% MoM
The approach
Architecture and data audit
Search optimization (embeddings)
Intelligent cache + efficient context
Outcome
Your PoC works.
In production, it can fail.
There is a real gap between a demo and production: real users, real data, and edge cases. That is where errors, latency, and unpredictable costs show up.
My work begins where tutorials end: turning AI into reliable operations with metrics, control, and visibility.
Reputational Risk
If the model invents financial or legal information, the damage is reputational. In production you need controls, evidence, and consistent responses.
Broken Unit Economics
Without context control and smart reuse, cost per query scales with usage. What was a 'cheap demo' becomes an unsustainable margin.
Unstable P99 Latency
Averages lie: a small % waiting 10-15s is enough to break the flow. In production, stability at the worst percentiles matters.
Operational Blindness
Without traces, metrics, and logs, incidents are solved blind. You need per-request visibility: cost, latency, sources, and failures.
Precise Intervention.
No generalities.
"Less complexity. More reliability."
- Design Principle
Due Diligence & Architecture
Deep diagnostic of your current system: architecture, data, costs, and risks. We identify what prevents scaling and what to change first to operate with control.
- Prioritized risk map with immediate actions
- Cost model by volume and monthly projection
- Security review and access to critical data
- Prompt review and response policies
- Target architecture with key decisions
- 30/60/90-day roadmap with estimated impact
Observability Infrastructure
I turn AI into a visible, controllable system. I measure quality, latency, and cost per request, with alerts when something degrades.
- Executive health dashboard: quality, latency, and cost
- End-to-end traceability per request
- Alerts when quality drops or cost rises
- Evaluation dataset for continuous testing
- Defined thresholds and service targets
- Incident playbook with metrics and owners
Knowledge Retrieval Engineering
I make the system find the right information and respond consistently. Fewer wrong answers, less latency, and lower cost per query.
- Answers with clear, verifiable sources
- Better knowledge retrieval and less "noise"
- Intelligent cache to reduce cost and accelerate
- Continuous quality evaluation with real cases
- Knowledge update pipeline
- Measurable reduction in latency and cost per query
Technical Leadership (Fractional CTO)
Technical leadership to make fast, correct decisions. I align product, engineering, and vendors to deliver with quality and predictability.
- Engineering standards and delivery quality
- Architecture review and critical risks
- Technical selection and negotiation with vendors
- Technical roadmap with milestones and priorities
- Support on technical hiring and key interviews
- Execution cadence: rituals, metrics, and follow-up
Santiago Guerra
AI Infrastructure Strategy
"I design and optimize AI systems that run reliably in production."
Building AI today is fast. Operating it well in production is different: data shifts, edge cases appear, and pressure on security and costs grows. That is where trust with customers is won or lost.
I work on systems already running or about to launch: I identify bottlenecks, quality failures, and unnecessary cost sources. I implement continuous evaluation, observability, and retrieval improvements to reduce wrong answers, latency, and uncertainty.
I integrate as an independent technical partner to make decisions with data, not assumptions. I deliver dashboards and standards your team can operate - what to measure, what to alert on, and what to optimize first. The goal is clear: stability, cost control, and reliable operations.
Let's build infrastructure
for production.
I work with companies that need reliable AI in operation: security, controlled costs, and stable performance. If that is a priority, let's talk.
Response within 24h for corporate inquiries.