You will get a custom AI agent POC: RAG, tool calling, guardrails
Project details
Most AI agents work in the demo and fail in production. I build the version that survives. I'll design and build a working AI agent for one workflow in your business - it reads your data, reasons about it, and acts through your tools (CRM, email, databases, APIs). Built on OpenAI, Anthropic Claude, or open-source models. The difference: an eval suite that proves correct behavior before launch, guardrails that constrain actions, and confirmation gates - how I build agents as lead engineer on a consumer AI product. You get documented code you own, an eval report, and a plain-English handover.
AI Algorithms
Convolutional Neural Network, Generative Adversarial Network, Large Language Model, Long Short-Term Memory Network, Multilayer Perceptron, Multimodal Large Language Model, Recurrent Neural Network, Regression Analysis, Self-Organizing Map, Transformer ModelAI Applications
AI Chatbot, AI Mobile App Development, AI Text-to-Image, AI Text-to-Speech, AI-Generated Code, AIOps, Image Processing, Object Detection, Synthetic Data Generation, Text Recognition, Time Series Analysis, Time Series ForecastingAI Development Language
PythonAI Models
ChatGPT, DALL-E, Dolly, GPT-3, GPT-4, GPT-Neo, Jurassic-2, LLaMA, Midjourney AI, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$1,950
|
Standard
$2,950
|
Advanced
$4,950
|
|---|---|---|---|
| Delivery Time | 14 days | 21 days | 30 days |
Number of Revisions | 1 | 2 | 2 |
AI Model Integration | |||
Batch Normalization | |||
Database Integration | |||
Detailed Code Comments | |||
Image Upscaling | |||
MLOps | |||
Model Deployment | |||
Model Documentation | |||
Model Monitoring | |||
Model Testing & Optimization | |||
Model Tuning | - | ||
Natural Language Processing | |||
NLP Tokenization | |||
Pre-Training | |||
Prompt Engineering | |||
Setup File | |||
Source Code |
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DD
Dawson D.
Dec 18, 2022
Backend for Webapp
Anas worked fast and communicated frequently and made sure I was updated. His code is clean and well documented, it was a pleasure to work with him.
About Anas
Agentic AI Engineer | AI Agents, Automation, RAG & LLM Apps
Islamabad, Pakistan - 6:29 am local time
Most AI agents break the moment they meet real users, real data, and real edge cases. I build the unglamorous parts that make them survive: evals, guardrails, fallbacks, confirmation gates, and clean integration into your existing stack - so you get a system you can trust, not a black box you're afraid to touch.
WHAT I BUILD
• Autonomous AI agents & multi-agent systems - tool/function calling, orchestration, memory
• RAG systems & AI chatbots grounded in your documents and live app data, with cited answers
• LLM features inside existing products (OpenAI, Anthropic Claude, Gemini, open-source)
• Agent guardrails, evals & observability - so you can see and trust what's running
• The backend behind it all: Node.js, NestJS, Go, PostgreSQL, Redis, Kafka, GCP
PROOF
I currently lead engineering for a consumer family-safety AI product: I architected the context layer that grounds the assistant in live app state, designed the guardrails that let agents act safely on a parent's behalf, and scaled to 30+ audited agent actions in production. Earlier: cut an API's latency 70% (1.2s to ~350ms) for a platform serving 1,000+ users, and shipped checkout features that helped a fintech startup close a $10M round. On Upwork: $50K+ earned across long-term engagements, 5.0 rating, 1,900+ hours.
HOW I WORK
I start with the workflow, not the tech. If an agent pays for itself, I'll tell you how I'd build it - architecture, effort, and monthly running costs. If it doesn't, I'll tell you that too, before you spend money. Every build ships with evals, monitoring, documentation, and a clean handover. I also write about agent reliability, observability, and memory vs. context on my engineering blog.
Have a manual, repetitive, expensive workflow that should run itself - or an AI agent that isn't behaving in production? Message me with what's eating your team's time, and I'll tell you exactly how I'd approach it.
Steps for completing your project
After purchasing the project, send requirements so Anas can start the project.
Delivery time starts when Anas receives requirements from you.
Anas works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Gathering
Discussions with various stakeholders to define system and DoD
Execution
Work in progress with timely updates