You will get Schema Markup + JSON-LD for AI Search (Up to 100 Entities)
Project details
Most sites have zero schema markup or only the auto-generated default. AI platforms use structured data to understand who you are and whether to cite you. Without proper schema, you are functionally invisible to AI synthesis.
I deploy schema entities across your site using Claude Code for speed and validation. Every entity is validated against Google Rich Results before delivery.
Schema types I implement:
• Organization (sameAs, address, contact, logo)
• Person (founder/author profiles, sameAs to LinkedIn/X/GitHub)
• Article and BlogPosting
• FAQPage (auto-extracted from FAQ sections)
• Product and Service
• BreadcrumbList
• SpeakableSpecification (for voice/AI assistant readouts)
• HowTo, Review, Event, Course, JobPosting (when applicable)
CMS support: WordPress, Webflow, Next.js / Nuxt / Astro, Shopify, custom static sites.
What you get:
• Schema entities deployed across your site
• Validation report (every entity passes Google Rich Results test)
• Reference document showing where each entity lives
• Maintenance guide for your team to extend without breaking
I deploy schema entities across your site using Claude Code for speed and validation. Every entity is validated against Google Rich Results before delivery.
Schema types I implement:
• Organization (sameAs, address, contact, logo)
• Person (founder/author profiles, sameAs to LinkedIn/X/GitHub)
• Article and BlogPosting
• FAQPage (auto-extracted from FAQ sections)
• Product and Service
• BreadcrumbList
• SpeakableSpecification (for voice/AI assistant readouts)
• HowTo, Review, Event, Course, JobPosting (when applicable)
CMS support: WordPress, Webflow, Next.js / Nuxt / Astro, Shopify, custom static sites.
What you get:
• Schema entities deployed across your site
• Validation report (every entity passes Google Rich Results test)
• Reference document showing where each entity lives
• Maintenance guide for your team to extend without breaking
Industry Expertise
HR & Business Services, Real Estate, Retail & Consumer Goods, Tech & ITLanguage
EnglishWhat's included
| Service Tiers |
Starter
$500
|
Standard
$1,000
|
Advanced
$2,500
|
|---|---|---|---|
| Delivery Time | 5 days | 7 days | 14 days |
Title Optimization | - | - | |
H1, H2, H3 Tags | - | - | |
Meta Description | - | - | |
Image Alt Tags | - | - | |
Schema Markup | |||
Page Audit | - |
About Badal
Senior AI Engineer | AI Agents + RAG, Voice Agent, GEO/AEO
Bengaluru, India - 8:46 pm local time
I led the technical build at two AI-first startups:
▸ An AI candidate sourcing platform running 800M-profile vector search in production (Qdrant + hybrid retrieval + cross-encoder reranking, sub-100ms latency), and
▸ A GEO/AEO audit platform monitoring AI visibility of any brand across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews.
My niche is the 20% custom AI work that off-the-shelf SaaS can't deliver. I focus on systems that actually ship to production with eval harnesses, observability, retry logic, and cost controls. Not POCs that rot in a sandbox.
Stack: Python, Claude Sonnet 4, OpenAI GPT-5, Qdrant, vLLM, n8n, FastAPI, LangChain, LangGraph, Portkey/Langfuse for observability.
What I deliver:
▸ Custom AI Agents. Multi-step Claude or OpenAI agents with proper orchestration, eval harnesses, retry logic, and observability. LangChain, LangGraph, or custom Python. Production-ready in 3-4 weeks.
▸ Production RAG Systems. Hybrid retrieval (dense + sparse + RRF fusion + cross-encoder reranking) with eval harness across your real corpus. Stack flexibility on vector DB (Qdrant, Pinecone, Weaviate, pgvector) and LLM (Claude, OpenAI, Gemini).
▸ Custom Support Chatbots. RAG over your docs AND ticket history. The systems Intercom Fin, Ada, and Zendesk AI can't deliver because they need deeper integration. Includes deflection-rate eval before launch.
▸ GEO / AEO Audit + Implementation. Get your brand cited when buyers ask ChatGPT, Claude, Perplexity, Gemini, or Google AI Overview about your category. 10-dimension audit, schema markup, llms.txt setup, citation strategy. Monthly retainer option for ongoing visibility tracking.
▸ n8n / Make Workflow Automation. The engineering-depth tier with custom Claude or OpenAI nodes, retry logic, observability, and Python sub-workflows. For projects that outgrew drag-and-drop.
▸ Cold Outreach + Lead-Gen Pipelines. Apollo + Instantly + Smartlead + Claude personalization. Account research agents that take a company URL and output decision-makers + intent signals + outreach angle. Built scraping infrastructure handling 5M+ records/day with anti-bot circumvention.
▸ Custom Sourcing Agents for Recruiting Firms. Multi-source candidate search beyond LinkedIn and Indeed, with custom scoring matched to your hiring criteria. For boutique recruiting firms with real engineering budget.
How I work:
1. 30-min discovery call to find the actual bottleneck. Most prospects describe the symptom, not the root cause.
2. Fixed-scope quote with one round of revision included. You know the price before we start.
3. Weekly Loom updates plus Slack or Notion for ongoing work.
4. Ship to production with eval harness, observability, and 30 days of post-launch bug-fix support.
Steps for completing your project
After purchasing the project, send requirements so Badal can start the project.
Delivery time starts when Badal receives requirements from you.
Badal works on your project following the steps below.
Revisions may occur after the delivery date.
Plan, generate, deploy schema
Audit existing schema, plan which entities to add, generate JSON-LD using Claude Code, validate against Google Rich Results, deploy to your CMS, deliver reference doc.