You will get ML Prediction for Chemical Reaction Networks & Web Interface
Project details
I will build Alphakinetics, a specialized machine learning system designed to predict complex chemical reaction networks. This is not just a script; it is a full-stack scientific tool. I use Graph Neural Networks (GNNs) or Transformer models to analyze molecular structures and predict reaction outcomes. The final tier includes a user-friendly web interface where researchers can input molecules and visualize reaction pathways in real-time.
Machine Learning Tools
Keras, scikit-learnWhat's included
| Service Tiers |
Starter
$56
|
Standard
$89
|
Advanced
$121
|
|---|---|---|---|
| Delivery Time | 4 days | 10 days | 15 days |
Number of Revisions | 0 | 0 | 0 |
Model Validation/Testing | - | - | - |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
About Isaac
Full Stack AI Engineer | n8n, RAG, LangChain, Open AI | AI Agents
Lagos, Nigeria - 2:36 pm local time
But you can just message me, I’ll make it zoom 🚀
Full Stack AI Engineer | n8n, RAG, LangChain, OpenAI | AI Agents
I build production-ready AI systems that actually solve business problems, not toys. From orchestration with n8n to Retrieval-Augmented Generation (RAG) powered by LangChain and OpenAI, I design scalable pipelines, intelligent agents, and automation that save time, reduce errors, and unlock new product capabilities.
Here’s the reality:
🚨 Manual workflows, brittle automations, and half-built ML proofs-of-concept are costing you time and opportunities.
Many teams struggle to move from research to reliable production: fragmented integrations, slow retrieval, hallucinations in LLM responses, and no observability. I fix that.
What I do (end-to-end)
I’m Isaac, a Full Stack AI Engineer who bridges product, ML, and backend engineering. I deliver systems that are maintainable, secure, and built for scale.
Core services
→ RAG & LangChain pipelines: design and implement retrieval, chunking, embedding, and prompt chains that return accurate, grounded answers.
→ n8n automation: orchestrate data flows, triggers, and system integrations so business workflows run without manual hand-holding.
→ OpenAI & LLM work: prompt engineering, fine-tuning workflows, safety/guardrails, and API-based deployments.
→ AI Agents: build goal-directed agents that interact with APIs, databases, and users to automate complex tasks.
→ Vector DB & embeddings: integrate and tune vector stores (search, filtering, hybrid retrieval) for fast, relevant results.
→ Backend & frontend: APIs, microservices, and simple UIs to expose AI features to users and apps.
→ MLOps & monitoring: model/version management, logging, retraining triggers, and latency/quality SLAs.
→ Integrations: connect CRMs, Slack, WhatsApp, databases, ERP systems, anything with an API.
→ Proof-of-Concept → Production: rapid POC to validate value, then harden for reliability, cost, and security.
Typical workflow (how we’ll work together)
Discovery call: goals, KPIs, constraints.
System audit: review current infra, data, and bottlenecks.
Blueprint & estimate architecture, milestones, and deliverables.
Prototype / POC: quick demo to validate approach (RAG demo, agent flow, n8n workflow).
Implementation: production-grade code, infra-as-code, tests, and CI/CD.
Review & iterate: you test, I refine until it meets KPIs.
Launch, docs & training: handover, runbooks, and team training.
Post-launch support: monitoring, improvements, and cost/quality tuning.
Why clients work with me
→ I combine ML intuition with software engineering discipline, so models behave reliably in production.
→ Clear, frequent communication and well-documented code.
→ Focus on measurable outcomes: latency, accuracy, automation time-saved, or revenue impact.
→ Practical experience deploying LLMs, agent loops, and automation flows end-to-end.
Clients consistently tell me they value fast iterations, clean APIs, and automations that actually reduce workload, not add more moving parts.
Ready to ship a reliable AI feature, agent, or automation? Hit Message and tell me your biggest AI automation problem, I’ll reply with a focused plan and next steps.
Cheers,
Isaac, Full Stack AI Engineer (n8n • RAG • LangChain • OpenAI • AI Agents)
Steps for completing your project
After purchasing the project, send requirements so Isaac can start the project.
Delivery time starts when Isaac receives requirements from you.
Isaac works on your project following the steps below.
Revisions may occur after the delivery date.
Project Review 1
Review project scope with clients to make sure we are on the same page concerning all project details after client submits project scope
Project Review 2
Review project scope with clients to make sure we are on the same page concerning all project deliverables before final delivery