You will get Agentic AI Solution – Tailored AI Agents for Real Use Cases
Project details
I’ll design and build a functional MVP of an AI agent tailored to your specific use case, sales, support, research, or beyond. Using LangChain, OpenAI, and modern agentic frameworks, I’ll create a goal-oriented AI that interacts with users or tools intelligently, giving you a demo-ready prototype for pitching, testing, or early integration.
AI Development Type
Knowledge RepresentationAI Development Language
PythonWhat's included $1,500
These options are included with the project scope.
$1,500
- Delivery Time 7 days
- Number of Revisions 1
About Cilia
AI Engineer | LLMs & Prompt Engineering | RAG | Agentic AI Solutions
Algiers, Algeria - 8:01 pm local time
As an AI/LLM engineer with almost 3 years of hands-on experience, I specialize in building reliable, purpose-driven solutions that streamline operations, enhance user experience, and unlock efficiency using language models and modern AI tools.
What I Work On:
🔹 LLM-Powered Applications – Building intelligent agents and chatbots that are grounded, context-aware, and aligned with user intent.
🔹 Retrieval-Augmented Generation (RAG) – Implementing pipelines that connect AI with your internal data through embeddings and vector search.
🔹 Prompt Engineering & System Logic – Designing structured, testable prompt flows that improve LLM output quality and reliability.
🔹 Backend Integration & Deployment – Using FastAPI, Docker, Twilio, and cloud infrastructure to bring AI solutions into production.
What Sets Me Apart:
• Balanced Technical Depth – I work with a modern AI stack, but always with simplicity, performance, and real use cases in mind.
• Clear Communication – I bring structure, transparency, and straightforward collaboration to every project.
• Continuous Learning – I stay close to the evolving AI landscape and bring that insight to every engagement.
• Practical Delivery – I focus on what works, scalable, maintainable code that integrates cleanly with your systems.
My Current Toolkit:
- AI & LLMs: OpenAI, Claude, LangChain, Langsmith, Hugging Face, RAG pipelines
- Backend: Python, FastAPI, Docker, Neo4j, GitHub Actions
- RAG Tools: FAISS, Qdrant, text-embedding-3-small, BM25 hybrid search
- Integrations: GoHighLevel, REST APIs
📚 I also write part-time on Medium, where I share practical thoughts and real-world lessons from working with AI systems, LLMs, and RAG architectures.
If you’re exploring how AI can support your team, product, or process, and want to approach it with clarity and purpose, I’d be happy to connect.
Steps for completing your project
After purchasing the project, send requirements so Cilia can start the project.
Delivery time starts when Cilia receives requirements from you.
Cilia works on your project following the steps below.
Revisions may occur after the delivery date.
Define Agent Role & Behaviors
Align on the agent’s goals, user persona, and key interactions.
Design Prompt & Toolchain
Create agent logic using LangChain and OpenAI with relevant tools.