Founder & Lead AI Systems Researcher, PulseHub Pro
Researching & Publishing Since 2024 · Madrid, Spain
Rodrigo Peña Vigil is the founder and editorial director at PulseHub Pro, where he leads empirical research into enterprise software ROI, LLM token pricing architectures, and financial technology governance. He is the author and architect of PulseHub Pro's financial audit engines and peer-reviewed benchmark datasets.
A Software Engineer and Data Science specialist from Universidad Politécnica de Madrid (UPM), Rodrigo directs the quantitative modeling frameworks used by CFOs and enterprise architecture teams to audit cloud seat waste, evaluate deterministic cybersecurity safeguards, and align machine-learning deployments with the NIST AI Risk Management Framework (AI RMF 1.0).
Prior to founding PulseHub Pro, Rodrigo conducted research in computational modeling, autonomous agent orchestration, and algorithmic systems optimization. He regularly collaborates with enterprise security engineers and financial operators to stress-test multi-model AI architectures against real-world budget constraints.
Background in Software Engineering and Data Science from Universidad Politécnica de Madrid (UPM). Rodrigo directs the peer-review methodology, mathematical modeling, and empirical benchmarking pipelines for all published reports on PulseHub Pro.
Every financial ROI formula, LLM token comparison matrix, and license consolidation strategy is audited under real enterprise budget constraints.
PulseHub Pro enforces strict editorial integrity. Rodrigo personally audits every report for factual accuracy, vendor claims verification, and primary citation grounding (NIST, ENISA, SEC filings, and peer-reviewed journals).
Read our full Editorial Independence Policy →Authored, reviewed, and calibrated by Rodrigo Peña Vigil (56 reports)
28-minute masterclass: Sandbox Model Context Protocol (MCP) servers with gVisor container isolation, enforce OIDC, and prevent injection.
26-minute masterclass: Build hybrid GraphRAG pipelines combining Neo4j knowledge graphs with vector embeddings for zero-hallucination research.
25-minute masterclass: Conduct adversarial red teaming on agentic AI workflows, prevent jailbreaks, and enforce zero-trust model guardrails.
An authoritative 25-minute masterclass on architecting, scaling, and securing enterprise Model Context Protocol (MCP) servers using stateless Streamable HTTP transport, OIDC token forwarding, and containerized gateway topologies.
An authoritative 24-minute masterclass on architecting GraphRAG engines: combine PostgreSQL PGvector dense embeddings with property knowledge graphs to achieve sub-10ms hybrid retrieval and eliminate hallucinations across 10,000+ enterprise documents.
An authoritative 22-minute masterclass on enterprise AI security: build adversarial red-teaming test suites, block indirect prompt injections in RAG pipelines, and enforce zero-trust cryptographic guardrails against unauthorized tool execution.
24-minute masterclass: Architect stateful multi-agent swarms, graph state machines, and durable execution pipelines in production.
Deploy real-time Graph AI AML screening for ISO 20022 payment rails. Reduce false positives by 85% and achieve sub-50ms transaction latency.
Deploy an enterprise AI gateway to automate multi-model token routing, prevent PII data leakage, and reduce LLM cloud inference spend by 45%.
Engineering architecture guide: Deploy orchestrator-worker agentic workflows to automate code synthesis, test execution, and sprint velocity.
Production deployment playbook: Serve open-weight LLMs on-premise using vLLM, FP8 quantization, and local hardware for 100% data sovereignty.
Step-by-step guide for researchers: Ground literature reviews with AI, eliminate hallucinations, and automate citation synthesis.
Lesson 1 of 5: Complete zero-to-launch playbook for students and creators to scope, build, and start any AI project with zero budget.
A comprehensive decision framework for founders and enterprise leaders to select the optimal AI models, vector stores, coding workspaces, and FinOps layers.
22-minute masterclass: Build zero-budget multi-model production AI pipelines, LLM routing, and enterprise security.
10-minute tutorial: Connect AI tools to automate notes, deep research, and daily workspace tasks with zero friction.
Security architecture guide: Secure generative AI pipelines in banking with zero-trust model isolation, prompt injection defense, and PII masking.
Step-by-step financial guide: Model enterprise AI ROI, calculate LLM payback timelines, and quantify net bottom-line yield for executive buy-in.
Stop wasting 15+ hours on manual spreadsheets. Compare the 10 best AI productivity tools built for finance teams and CFOs.
Quantify unutilized SaaS seats and reclaim enterprise software budget. Step-by-step cost optimization framework.
Negotiation strategy guide for enterprise procurement leads. Eliminate auto-renewal price hikes, lock in ELA true-up caps, and reclaim budget.
Strategic executive report on how 2026 CFOs balance AI-driven productivity gains with zero-trust cybersecurity and cloud cost governance.
Evaluate no-code AI platforms for legal teams. Automate contract analysis, streamline due diligence, and measure billable hour productivity gains.
Economic analysis of how enterprise AI productivity tools reduce remote team communication overhead, automate task routing, and scale output.
Engineering guide to LLM token optimization: Deploy prompt caching, context compression, and semantic routing to cut inference cloud spend by 60%.
Strategic analysis of the IBM and OpenAI enterprise partnership. What it means for hybrid cloud LLM serving, data privacy, and enterprise IT budgets.
Financial simulation framework to model multi-year AI SaaS cost escalation, consumption pricing risks, and enterprise budget forecasting.
Strategic roadmap for retail and commercial banks deploying AI-driven core banking systems, personal finance automation, and customer retention.
Strategic guide: Deploy AI for real-time cash flow forecasting, autonomous treasury management, and liquidity control.
Quantify true operational cost per AI agent transaction. Model token overhead, tool calling latency, vector DB queries, and cloud inference spend.
Deploy agentic Graph AI for real-time ISO 20022 transaction screening. Reduce compliance review friction and eliminate false positive fraud alerts.
Executive guide: Navigate the shift from per-seat software licenses to consumption pricing and control shadow AI.
Benchmark report: Compare deterministic state graphs versus conversational swarms to maximize engineering velocity.
CFO-focused benchmark report: Analyze enterprise AI credit underwriting, automated risk scoring, and net financial payback in fintech.
Comprehensive guide to high-impact fintech AI use cases in 2026. Explore quantitative ROI metrics, credit risk automation, and fraud prevention.
Analysis of IBM watsonx governance and multi-agent orchestration frameworks for enterprise AI deployment, hybrid cloud integration, and security.
Industry benchmark report analyzing how top-tier fintechs leverage AI for hyper-personalized banking, automated fraud, and risk scoring.
Benchmark report: Evaluate multi-agent orchestration frameworks, token consumption efficiency, circuit breaker patterns, and developer velocity.
Avoid auto-renewal price spikes. Executive guide to capping ELA true-up costs and negotiating enterprise SaaS contracts.
Comprehensive benchmark report: How market-leading fintechs and neobanks deploy AI for hyper-personalized banking, automated fraud, and risk analysis.
Step-by-step engineering guide: Deploy F5 agentic-ready AI gateways to enforce token rate limiting, zero-trust security, and cloud cost control.
Discover 10 high-margin AI use cases for fintech CFOs. Reduce operational expenditure, automate credit risk, and model exact financial payback.
Regulatory and operational playbook for Australian fintechs scaling AI infrastructure while maintaining APRA CPS 230 compliance.
Strategic framework for fintech executives to deploy generative AI, reduce customer acquisition cost (CAC), and maximize net ROI in 2026.
In-depth analysis of the Arga Labs report on enterprise AI agent training, fine-tuning accuracy, and synthetic dataset generation efficiency.
Lesson 2 of 5: Master the 5-step role-task-context framework for deterministic, high-precision AI outputs.
Lesson 3 of 5: Beginner guide to connecting AI to real-world tools, automating Notion databases, and consuming free web APIs.
Lesson 4 of 5: Complete 60-minute no-code MVP blueprint for students and creators to build and launch AI-powered web applications.
Lesson 5 of 5: Test AI accuracy, eliminate hallucinations, and launch your free cloud production endpoint.
10-minute tutorial: Synthesize 50+ research papers and financial PDFs into clean reports using NotebookLM and Claude.
10-minute tutorial: Run DeepSeek-R1 and Ollama locally on your laptop with zero cloud fees and 100% privacy.
10-minute tutorial: Extract unstructured PDF invoice data into clean Excel spreadsheets with zero formulas using AI web workflows.
10-minute tutorial: Deploy low-code autonomous AI agents using n8n and Groq with zero complex Python setup.
Production engineering playbook: Instrument multi-agent swarms with LangGraph tracing, OpenTelemetry metrics, and automated token budget circuit breakers.
Engineering playbook: Implement RAGAS quantitative evaluation gates, automated hallucination detection, and synthetic test suites in CI/CD pipelines.
Zero-trust security playbook: Sandbox Model Context Protocol (MCP) servers with gVisor, enforce OIDC authentication, and mitigate prompt injection.