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Felix Ibeamaka@Electroni6
1
Events attended
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Submissions made
3+ years of experience
About me
I help startups and businesses design, build, and scale AI systems that work in real-world production environments. My work spans multi-agent architectures, RAG pipelines, Q&A and customer support chatbots, machine learning models, and computer vision applications, taking ideas from concept to deployment. I have 3+ years of hands-on experience building and orchestrating multi-agent AI systems using LangGraph, LangChain, and CrewAI, building and integrating tools for autonomous planning and execution, and connecting agents to everyday platforms like WhatsApp and Google services. I also develop scalable, multi-tenant RAG pipelines for customer support Agents, train machine learning models using TensorFlow and scikit-learn, and deploy production-ready AI systems on cloud platforms such as Render, with a strong focus on reliability, scalability, and real business impact.
🤝 Top Collaborators
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🤓 Latest Submissions
Lobster Path
As enterprises rush to adopt Large Language Models (LLMs), they are exposing themselves to unprecedented security risks. Developers lack visibility into the data flowing between their applications and third-party AI providers like OpenAI or Anthropic. This creates massive vulnerabilities: malicious users can execute prompt injections or jailbreaks, while internal systems might accidentally leak sensitive PII or proprietary credentials. LobsterPath solves this by acting as a drop-in AI Security Operations Center (AI-SOC). Sitting as a seamless reverse proxy between your application and your chosen LLM provider, LobsterPath requires zero code changes—developers simply update their API Base URL and instantly gain enterprise-grade security. At the core of the platform is LobsterTrap, a high-performance Deep Packet Inspection (DPI) engine that secures data in both directions: Ingress Protection: Before a prompt ever reaches the LLM, LobsterTrap scans it for malicious intents—instantly blocking prompt injections, jailbreak attempts, malware generation requests, and social engineering patterns. Egress Protection: Before the LLM's response is returned to the user, the engine scans the output to ensure no Personally Identifiable Information (PII), financial data, or internal API keys are leaked. Beyond active threat prevention, LobsterPath brings total observability to AI. Every interaction is logged in a centralized dashboard, tracking latency, token usage, threat metadata, and the final security verdict. Security teams can manage multi-tenant project policies, instantly download comprehensive PDF compliance reports, and test the DPI engine's resilience in real-time using our interactive built-in Security Playground. LobsterPath transforms blind AI API calls into fully observable, auditable, and secure events—allowing enterprises to innovate with LLMs without sacrificing security or compliance.
19 May 2026
