You will get an AI Readiness Audit: one week, one PDF, one use case ready to build
Top Rated
Top Rated
Project details
In one week you get a clear, honest answer to a single question: is this AI use case worth building, and what's the fastest path to production? I'm a Staff Engineer who ships real AI agents (local LLMs, on-prem, EU AI Act-ready), not slide decks. I assess your use case against your actual stack, data, and privacy constraints, then hand you a focused PDF: feasibility, recommended architecture, risks, effort estimate, and a concrete build roadmap. No vendor lock-in, no OpenAI dependency unless you want it, and your data never has to leave your infrastructure. By Friday you'll know exactly whether to build, buy, or wait, and if you build, you'll have a use case scoped and ready to start.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AIOps, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Hugging Face, NVIDIA AI Platform, PyTorchAI Models
LLaMAWhat's included $3,500
These options are included with the project scope.
$3,500
- Delivery Time 7 days
- Number of Revisions 1
- Model Documentation
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MK
Markus K.
May 8, 2026
PHP Developer - Admin Tool Interfaces
One of the most reliable engineers I've worked with. Terry has been a key part of several projects over the last year, including AWS infrastructure security, browser extension monitoring, and scraping infrastructure. Consistently delivered without needing to be managed. Hand him a problem and he comes back with a working solution and a clear explanation. Strong technical range, fast turnaround, honest about tradeoffs. Hire him if you need a senior engineer who can run a project on their own.
IA
Ibtisam A.
Jan 28, 2025
Backend Developer (PHP) with DevOps Understanding
Highly skilled DevOps engineer with expertise in CI/CD pipelines, cloud infrastructure, and automation. His ability to streamline workflows, ensure seamless deployments, and maintain system reliability is outstanding.
PV
Philipe Achille V.
Aug 20, 2024
Integrate new grouping functionality into existing web app
JL
Jim L.
Apr 16, 2024
Custom Payments API Integration
KK
Khaled K.
Dec 27, 2023
Fix HMAC PHP
Excellent developer
About Ogbemudia Terry
AI Engineer | Production LLM Agents, On-Prem & EU AI Act-Ready
100%
Job Success
Bergisch Gladbach, Germany - 12:33 am local time
Most AI projects die in pilot purgatory: a few Slack bots, a Confluence plugin, nothing actually running. I take one real use case and get it into production: local LLM deployment, RAG, MCP tool integration, runbooks, and audit logs - on your infrastructure, so your data never has to leave it.
This matters most for engineering-led companies operating under European data and compliance constraints. Your telemetry, customer data, and postmortems stay on-prem. Every use case gets an EU AI Act risk classification. No vendor lock-in - MCP standard, swappable models.
13 years of software engineering, Top Rated Plus, 100% Job Success. Founder of TraceKit (production debugging/APM) and funkel.ai. I work the way it should be sold: fixed price, fixed scope, one engineer who strategizes, builds, and hands off cleanly.
Three ways to start:
• AI Readiness Audit - 1 week, one PDF, one use case ranked and ready to build
• Agent Build Sprint - 4–6 weeks, one use case to production, fixed price
• Embedded AI Engineer - fractional Staff Engineer on retainer inside your team
If you want production AI without the usual headaches, let's talk.
Steps for completing your project
After purchasing the project, send requirements so Ogbemudia Terry can start the project.
Delivery time starts when Ogbemudia Terry receives requirements from you.
Ogbemudia Terry works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery call & use case scoping
We align on the one AI use case to assess, your stack, data, and privacy/on-prem constraints.
Technical assessment & architecture
I evaluate feasibility, recommend a local/on-prem LLM architecture, and map risks, effort, and EU AI Act considerations.