HN
Haider N
Agentic Workflow Builder
5/5Outcome score
Request Introduction
NS
Engagements completed5
Avg engagement length30 days
KPIs achieved rate93%
Repeat engagement rate92%
Member since2026
Expertise
Verticals
B2B lead generation and sales technologyB2B SaaS and software technologyHealthcare technology
Skills
Agentic workflow developmentLLM integration and prompt engineeringRAG and knowledge retrievalLead research and outreach automationBackend engineering and REST APIsAsynchronous processing and cachingFull-stack application developmentPerformance optimization and analytics dashboards
Tool Stack
ReactNext.jsReact NativeTypeScriptJavaScriptHTMLCSSNode.jsExpress.jsFastAPIREST APIsPythonJavaPHPGitGitHub
Outcome Index breakdown
Based on structured outcome reviews from completed engagements. Not star ratings — actual KPI achievement data.
KPIs met or exceeded
4/5
Communication quality
4/5
Strategic contribution
4/5
Agent deployment effectiveness
4/5
Would engage again
4/5
Recent engagements
| Client | Tier | KPIs | Duration | Score |
|---|---|---|---|---|
| Byldd | Software Engineer | Built an automated Reddit lead discovery and outreach-drafting workflow that reportedly saved 10 hours per week. Reduced average backend response time from 123.8 ms to 1.7 ms using Redis caching, with P95 latency falling from 290 ms to 1 ms. Developed AI-powered chat features used by 500+ daily active users and an analytics dashboard covering 20+ community groups. Delivered a two-sided live-tracking system four days ahead of the estimated timeline. | August 2025–August 2026 | 5/5 |
| HashedBit Innovations | Software Engineer Intern | Reduced redundant frontend-backend interactions by 30%. Improved SQL query execution efficiency by 25%. Reduced feature turnaround time by 20%. | June 2025–July 2025 | 5/5 |
| Research Copilot | AI Workflow Developer | - Implemented a LangGraph-based research pipeline. - Integrated RAG with pgvector and PostgreSQL for source-grounded responses. - Added asynchronous execution, retries, job states, and streaming progress updates. - No quantified accuracy, time savings, or commercial adoption metrics are provided. | 2026 | 5/5 |
| InstaCap | Full Stack Developer / AI Application Developer | Built a speech-to-text caption pipeline using Deepgram and video rendering with Remotion. Implemented background processing using BullMQ and Redis, with rendering on AWS Lambda. Reported 25 users and 45 videos rendered at the time documented in the resume. | June 2026 | 5/5 |
About
Nayab builds AI-powered applications and automated workflows for software products and operational teams. He combines LLM integrations, agentic research pipelines, RAG, and asynchronous job processing to connect research, data retrieval, and workflow automation. At Byldd, he built a lead discovery and outreach workflow that reportedly saved 10 hours per week, alongside backend optimizations that reduced average response time from 123.8 ms to 1.7 ms.
Similar experts
KS
Kushbhargav S
Agentic Workflow Builder
5/5Outcome score
Request Introduction
MV
Mrunal V
SEO Specialist
5/5Outcome score
Request Introduction