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Technical SEO, AEO & GEO Engineering

Akshora AI Labs engineers high-performance technical SEO, Answer Engine Optimization (AEO), and Generative Engine Optimization (GEO) for modern Next.js and React enterprise platforms. We eliminate client-side JavaScript rendering penalties, optimize Core Web Vitals to sub-second FCP, implement deterministic Schema.org knowledge graphs, and deploy llms.txt endpoints so your product is accurately cited by Perplexity, ChatGPT, and Google AI Overviews.

What's included

  • Next.js App Router hybrid rendering optimization (SSR/SSG/ISR) for 100% Googlebot discoverability
  • Answer Engine Optimization (AEO) structuring for Perplexity AI, Google AI Overviews, and ChatGPT Search
  • LLMs.txt and Markdown knowledge endpoint deployment for AI web crawler indexing
  • Deterministic Schema.org connected JSON-LD knowledge graphs (Organization, Service, FAQ, Breadcrumbs)
  • Core Web Vitals audit and engineering (sub-800ms LCP, 0 CLS, INP under 100ms)
  • Server-side redirect architecture, canonical consistency, and XML sitemap hygiene

Common questions

What is the difference between traditional SEO and AEO / GEO?

Traditional SEO focuses on keyword ranking in traditional Google search result lists. Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) format your website's content and data structures so AI synthesis engines (like ChatGPT, Perplexity, and Google AI Overviews) extract and cite your brand as the primary factual answer.

Can you fix Next.js and client-side JavaScript indexing issues?

Yes. Our core engineering practice specializes in Next.js App Router architecture. We analyze initial HTML versus DOM hydration, configure optimal static generation, fix canonical inheritance, and eliminate rendering delay for search engine crawlers.

How do you implement llms.txt for enterprise applications?

We generate dynamic or static /llms.txt and /llms-full.txt endpoints according to the emerging LLM discoverability standard, packaging your company's core services, documentation, and pricing into clean, token-efficient Markdown for AI crawlers.

Common use cases

Concrete situations this service is actually built for.

  • B2B SaaS with client-side JavaScript rendering issues

    A modern SaaS app built with CSR is invisible to search engines because Googlebot defers JavaScript rendering. We refactor the routing architecture to Next.js SSG/SSR to ensure instant HTML indexing.

  • Enterprise brands losing citation in AI answer engines

    AI search engines (Perplexity, ChatGPT) hallucinate or omit company capabilities. We deploy structured llms.txt manifests and answer-first semantic data to secure high-authority AI citations.

  • E-commerce & directory scale crawl budget optimization

    A multi-thousand page platform suffers from crawl budget exhaustion and unindexed pages. We audit server response headers, eliminate redirect chains, and optimize canonical hierarchy.

One team, the whole stack

Technical SEO is an engineering discipline, not a marketing checklist. Our developers inspect server headers, build systems, edge CDNs, and AST transformers to guarantee technical compliance.

Frontend & Web

  • Next.js 14
  • React
  • TypeScript
  • JavaScript
  • Tailwind CSS

Backend & APIs

  • Node.js
  • Python
  • FastAPI
  • Express.js

Mobile App Development

  • React Native
  • Flutter
  • Dart
  • Expo

AI & Machine Learning

  • PyTorch
  • TensorFlow
  • OpenCV
  • TensorRT
  • LlamaIndex
  • LangChain

Databases & Vector

  • PostgreSQL
  • MongoDB
  • Redis
  • Qdrant
  • Elasticsearch

Cloud & DevOps

  • Docker
  • Kubernetes
  • AWS
  • Google Cloud
  • GitHub Actions CI/CD
  • Nginx

Is this you?

  • Is your React or Next.js website struggling to get indexed in Google Search Console?
  • Are AI answer engines like Perplexity or ChatGPT ignoring or misrepresenting your business?
  • Are slow Core Web Vitals and client-side rendering bottlenecks hurting your search visibility?

Akshora AI Labs bridges software engineering and search engine indexing. We diagnose crawl barriers, refactor Next.js rendering pipelines, and implement deterministic AEO knowledge graphs to maximize search capture.

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