You will get Autonomous Team-of-Agents for HackerNews Intelligence
Project details
Cut through tech noise with an autonomous, bias-reduced, fact-checked HackerNews research system. Using a specialized Team-of-Agents workflow, I build a fully automated research desk that continuously scouts trending stories, analyzes full content, verifies core claims, and produces professional, citation-rich briefs. Unlike one-off scraping or manual research, this system ensures redundancy, high factual accuracy, and traceable sources. Flexible LLM integration (OpenAI GPT-4o for speed or Ollama Llama3 for private/local runs) allows cost-effective and secure operations. Deliverables include executive briefs, blog drafts, and social-ready insights saving you hours of research while keeping you informed with actionable, trustworthy tech intelligence.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Content Creation, AI-Enhanced Classification, AIOps, Automatic Speech Recognition, Conversational AI, Natural Language Generation, Natural Language Understanding, Neural Machine Translation, Sentiment AnalysisAI Development Language
PythonAI Models
BERT, ChatGPT, GPT-3, GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$900
|
Standard
$1,800
|
Advanced
$3,000
|
|---|---|---|---|
| Delivery Time | 7 days | 12 days | 18 days |
Number of Revisions | 1 | 3 | 5 |
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 |
Frequently asked questions
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JP
Jeremy P.
Mar 19, 2026
Pyton script maintenance
He is great. Does good work keep me updated on any issues questions or slow downs. And if I have a question he always responds promptly. Great resource for our brand definitely recommend
JP
Jeremy P.
Dec 2, 2025
Parting Line height modifications on the creator
This was a great experience. He paid great attention to detail and guided me through the process the whole way. I will defiantly be back for more work! Recommend highly!
About Mehtab
Senior AI Solutions Architect | Generative AI, RAG & LLMOps Expert
100%
Job Success
Karachi, Pakistan - 7:35 pm local time
Stop wasting budget on hallucinating chatbots and slow prototypes. I architect high-performance multi-agent workflows and enterprise RAG pipelines that deliver measurable ROI not just code.
Most AI projects fail because of high latency, low accuracy, and poor coordination. I bridge that gap by building production-grade systems that are cost-efficient, lightning-fast, and battle-tested for real-world complexity.
𝗠𝘆 𝗖𝗼𝗿𝗲 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲
𝗛𝗶𝗲𝗿𝗮𝗿𝗰𝗵𝗶𝗰𝗮𝗹 𝗠𝘂𝗹𝘁𝗶-𝗔𝗴𝗲𝗻𝘁 𝗦𝘆𝘀𝘁𝗲𝗺𝘀
I design autonomous agent teams using CrewAI and LangGraph where coordinators manage workflow orchestration while specialized sub-agents handle research, analysis, and execution. These systems solve complex problems like real-time meeting intelligence, customer support routing, and automated development without constant supervision.
𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲-𝗚𝗿𝗮𝗱𝗲 𝗥𝗔𝗚 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲
Building hallucination-resistant knowledge engines using LangChain, LlamaIndex, and ClickHouse for ultra-fast vector search. My implementations handle 10,000+ documents with sub-second latency through hybrid search, semantic chunking, and intelligent re-ranking.
𝗙𝘂𝗹𝗹-𝗖𝘆𝗰𝗹𝗲 𝗟𝗟𝗠𝗢𝗽𝘀 & 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲
Engineering robust MLOps pipelines with Docker, Kubernetes, and NVIDIA Triton. I implement circuit breakers, evaluator patterns, and real-time monitoring using ClickHouse for unparalleled query speed and observability. Every system includes token tracking, cost alerts, and failure prevention.
𝗠𝗼𝗱𝗲𝗹 𝗙𝗶𝗻𝗲-𝗧𝘂𝗻𝗶𝗻𝗴 & 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻
Customizing open-source models (Llama 3.1, Mistral, Granite 4.0) using LoRA/PEFT and federated fine-tuning for domain-specific performance. I optimize inference pipelines with vLLM and TensorRT-LLM, achieving up to 23x throughput improvements.
𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 & 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲
Implementing multi-factor authentication, role-based access control, and ISO 42001 compliance frameworks. My systems include audit trails, encrypted data handling, and cryptographic signing for model provenance.
𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻
Applying CNNs and YOLOv8 for real-time object detection and vision-to-decision pipelines in specialized use cases.
𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗦𝘁𝗮𝗰𝗸
𝗠𝗼𝗱𝗲𝗹𝘀: 𝗚𝗣𝗧-𝟰𝗼, 𝗖𝗹𝗮𝘂𝗱𝗲 𝟯.𝟱, 𝗟𝗹𝗮𝗺𝗮 𝟯.𝟭, 𝗠𝗶𝘀𝘁𝗿𝗮𝗹, 𝗚𝗲𝗺𝗶𝗻𝗶
𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀: 𝗖𝗿𝗲𝘄𝗔𝗜, 𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵, 𝗟𝗮𝗻𝗴𝗖𝗵𝗮𝗶𝗻, 𝗟𝗹𝗮𝗺𝗮𝗜𝗻𝗱𝗲𝘅
𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻: 𝘃𝗟𝗟𝗠, 𝗧𝗲𝗻𝘀𝗼𝗿𝗥𝗧-𝗟𝗟𝗠, 𝗡𝗩𝗜𝗗𝗜𝗔 𝗧𝗿𝗶𝘁𝗼𝗻, 𝗠𝗼𝗱𝗲𝗹 𝗤𝘂𝗮𝗻𝘁𝗶𝘇𝗮𝘁𝗶𝗼𝗻
𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲: 𝗖𝗹𝗶𝗰𝗸𝗛𝗼𝘂𝘀𝗲, 𝗤𝗱𝗿𝗮𝗻𝘁, 𝗣𝗶𝗻𝗲𝗰𝗼𝗻𝗲, 𝗗𝗼𝗰𝗸𝗲𝗿, 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀, 𝗔𝗪𝗦/𝗚𝗖𝗣
𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: 𝗻𝟴𝗻, 𝗭𝗮𝗽𝗶𝗲𝗿, 𝗣𝘆𝘁𝗵𝗼𝗻 (𝗙𝗮𝘀𝘁𝗔𝗣𝗜/𝗙𝗹𝗮𝘀𝗸)
𝗪𝗵𝘆 𝗪𝗼𝗿𝗸 𝗪𝗶𝘁𝗵 𝗠𝗲
Production Focus: I build for scale with systems that maintain 99.9% accuracy under real-world load. Every solution includes error handling, retry logic, and comprehensive monitoring.
𝗖𝗼𝘀𝘁 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻:
Reduce token costs by 40-70% through intelligent caching, prompt compression, and strategic model selection. Full transparency with consumption tracking and budget alerts.
Coordination Complexity Solved: I handle the hardest part of multi-agent systems ensuring agents communicate effectively, avoid redundant work, and maintain state consistency across distributed workflows.
𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗙𝗶𝗿𝘀𝘁:
Every build includes clear architecture maps, runbooks, and repeatable processes so your team can maintain and scale what I build.
𝗣𝗿𝗼𝘃𝗲𝗻 𝗥𝗢𝗜:
My clients see 12-18 month competitive advantages through early adoption of sophisticated multi-agent architectures that are rapidly becoming industry standard.
𝗥𝗲𝗮𝗱𝘆 𝘁𝗼 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁 𝗮 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗔𝗜 𝘀𝘆𝘀𝘁𝗲𝗺 𝘁𝗵𝗮𝘁 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘀 𝗺𝗲𝗮𝘀𝘂𝗿𝗮𝗯𝗹𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝘃𝗮𝗹𝘂𝗲? 𝗟𝗲𝘁'𝘀 𝗱𝗶𝘀𝗰𝘂𝘀𝘀 𝘆𝗼𝘂𝗿 𝗿𝗼𝗮𝗱𝗺𝗮𝗽 𝗶𝗻 𝗮 𝟭𝟱-𝗺𝗶𝗻𝘂𝘁𝗲 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆 𝗰𝗮𝗹𝗹.
Steps for completing your project
After purchasing the project, send requirements so Mehtab can start the project.
Delivery time starts when Mehtab receives requirements from you.
Mehtab works on your project following the steps below.
Revisions may occur after the delivery date.
Setup & Configuration
Configure LLM access, input target focus keywords, and set Editor tone preferences.
Agent Deployment
Implement the Scout, Analyst, Fact-Checker, and Editor agents using the Team-of-Agents pattern.