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Fiverr Pro
English
$
USD
I will audit your ai rag architecture and create an implementation roadmap
Aleksey E.
About this gig
I will review your AI/RAG concept or existing system and deliver a practical architecture audit with a prioritized implementation roadmap.
The review can cover:
model and provider selection
RAG and retrieval strategy
data and vector storage
PostgreSQL / pgvector
API and system integration
local, cloud or hybrid deployment
privacy and data boundaries
reliability risks
cost and complexity trade-offs
You will receive clear recommendations on what to keep, change, defer and implement first based on your actual use case and constraints.
Included:
requirements and initial assessment
high-level technical architecture
data strategy
model/provider recommendations
prioritized implementation roadmap
one 30-minute consultation
Not included:
full application development
production deployment
penetration testing or certification
custom foundation-model training
transfer of proprietary reusable architecture or source code
Implementation work can be quoted separately after the audit.
Get to know Aleksey E.
Aleksey E.
Software Developer Python, APIs, PostgreSQL, AI and RAG
- FromBulgaria
- Member sinceSep 2025
- Avg. response time1 hour
Languages
Bulgarian, English, Russian
I help clients fix, finish and improve software applications and build clearly scoped AI/RAG integrations. I work with Python, JavaScript/TypeScript, APIs, PostgreSQL, databases, debugging and AI systems. I also have hands-on experience building a private cross-platform AI system with RAG, pgvector, model integration, testing, backup/restore and local/cloud deployment.
My Portfolio
FAQ
Is coding or implementation included?
No. This gig covers architecture review, technical recommendations and an implementation roadmap. Development, integrations and deployment are scoped separately.
Can you review an existing AI or RAG system?
Yes. I can review a concept, prototype or bounded existing system using the documentation, architecture notes and technical context you provide.
Can you review local, private or hybrid AI options?
Yes. The audit can compare local, cloud and hybrid approaches, including privacy, data control, model/provider choice, deployment constraints and trade-offs.
What information do you need before starting?
I need your use case, current system or concept, goals, constraints, relevant documentation, preferred providers or models if any, and known technical problems or risks.
