Question 1

What types of AI projects does Pharosyne work on?

Accepted Answer

Pharosyne specializes in multi-agent systems, RAG (Retrieval-Augmented Generation) architectures, voice AI agents, and custom AI/ML solutions. The focus is on enterprise-grade implementations that deliver measurable business value. With 19+ years of software engineering experience and leadership roles at companies like BBVA, Santander, and El Corte Inglés, Pharosyne brings proven expertise to complex AI challenges.

Question 2

Does Pharosyne offer fractional CTO or advisory services?

Accepted Answer

Yes, Pharosyne provides fractional CTO and Head of AI services for companies that need strategic technical leadership without a full-time commitment. This includes architecture guidance, team mentoring, and technology roadmap development.

Question 3

What is the typical engagement model?

Accepted Answer

Pharosyne offers flexible engagement models including project-based consulting, retainer arrangements, and fractional leadership roles. Each engagement starts with a discovery call to understand your needs. You work directly with senior architects, no account managers or intermediaries.

Question 4

Does Pharosyne work with startups or only enterprises?

Accepted Answer

Pharosyne works with both. The sweet spot is mid-market companies and growth-stage startups with complex technical challenges. Pharosyne also supports enterprises looking to modernize their AI and software architecture.

Question 5

What is RAG architecture and when should I use it?

Accepted Answer

RAG (Retrieval-Augmented Generation) combines large language models with your own data sources to provide accurate, contextual responses. It's ideal for building internal knowledge bases, customer support systems, or any AI application that needs access to proprietary information. Pharosyne has implemented RAG systems for enterprise clients handling millions of documents.

Question 6

How do multi-agent AI systems work?

Accepted Answer

Multi-agent systems use multiple AI agents working together to solve complex tasks. Each agent specializes in a specific function, and they collaborate to achieve goals that would be too complex for a single agent. Pharosyne designs and implements these systems for workflow automation, research pipelines, and autonomous business processes.

Question 7

What languages and technologies does Pharosyne use?

Accepted Answer

Pharosyne works primarily with TypeScript, Python, React, and Next.js for full-stack development. For AI/ML, the team uses OpenAI, Anthropic Claude, LangChain, and custom model implementations, with deep experience in vector databases like Qdrant, Weaviate, and pgvector for RAG systems.

Question 8

Does Pharosyne work remotely or on-site?

Accepted Answer

Pharosyne works primarily remotely from the EU (Spain), serving clients globally. For key workshops or critical project phases, on-site engagements within Europe are available. Remote work allows focus on delivery while maintaining flexible communication across time zones.

INSIGHTS

Workflows agénticos: guía práctica de implementación

Cuándo necesitas realmente un CTO fraccional (y cuándo no)

RAG vs fine-tuning: cuándo usar cada uno (y cuándo no usar ninguno)

Sistemas multi-agente: cuándo tienen sentido y cuándo no