I am an experienced elasticsearch, logstash and kibana consultant with a passion for getting meaning out of data. I have helped to setup and maintain large and small installations, from small pilot web sites upto TB clusters for multinational companies, on AWS and Google Cloud. Main technlogies: Non relational database: Elasticsearch Relational database: mySQL, postgres SQL Visualization: Kibana, Grafana Ingestion: Logstash, SQS Web server: Nginx Scripting: Python, PHP, AWS Lambda OS: Ubuntu AWS, cloudwatch, EC2, IAM, SQS

Welcome! Your Elasticsearch & OpenSearch Expert Looking for a reliable expert to design, optimize, or troubleshoot Elasticsearch or OpenSearch platforms? I’m Eraste Akande, Elastic Certified Engineer and Elastic Gold Contributor, with strong experience delivering scalable, high-performance search, observability, and analytics solutions. I help companies turn complex data into fast, reliable, and actionable systems, from cluster architecture to production-ready pipelines. What I Do Best? I design and optimize end-to-end Elastic & OpenSearch solutions, including: - Elasticsearch & OpenSearch cluster architecture and scaling - Migration from relational or NoSQL databases to Elasticsearch / OpenSearch - Elasticsearch ↔ OpenSearch migrations (both directions) - Search, analytics, and observability use cases - Log and event ingestion pipelines - Performance tuning and troubleshooting - Automation and integrations using Python Technologies I work with daily: Elasticsearch, OpenSearch, Logstash, Beats, Kibana, OpenSearch Dashboards, Kafka, Python Why Clients Choose Me ? ✅ Elastic Certified Expert Elastic Certified Engineer (since 2022) Elastic Certified Observability Engineer (2025) Elastic Certified Analyst (2025) ⭐ Elastic Gold Contributor Recognized by Elastic for consistent contributions, technical support, and knowledge sharing across the community. 🔄 Migration Specialist I help organizations safely migrate: - Relational databases (PostgreSQL, MySQL, SQL Server, Oracle) → Elasticsearch / OpenSearch - NoSQL databases (MongoDB, Cassandra, etc.) → Elasticsearch / OpenSearch - Elasticsearch → OpenSearch - OpenSearch → Elasticsearch With minimal downtime, zero data loss strategies, and performance validation. 🔍 OpenSearch Specialist Hands-on expertise in OpenSearch cluster setup, optimization, dashboards, and ingestion pipelines as a flexible and cost-effective alternative. 🐍 Python-Driven Automation I use Python to automate indexing, optimize queries, integrate third-party systems, and build efficient custom workflows. 🔧 End-to-End Delivery From architecture design to production optimization, I provide complete, tailored solutions — not just advice. 🤝 Client-Focused Approach I prioritize performance, scalability, and maintainability, ensuring solutions that grow with your business. Services I Offer - Elasticsearch / OpenSearch Cluster Setup & Optimization - Database → Elasticsearch / OpenSearch Migration - Elasticsearch ↔ OpenSearch Migration - Search & Analytics Architecture Design - Custom Kibana / OpenSearch Dashboards - Log & Event Ingestion Pipelines (Logstash, Beats) - Performance Tuning & Troubleshooting - Python Automation & Integrations Let’s Work Together If you need an expert who understands both the technical depth and real business impact of Elasticsearch and OpenSearch, including complex migrations, you’re in the right place. 📩 Message me today and let’s build or migrate your data platform with confidence.

I build agentic AI systems that run in production - not prototypes. A couple of years ago my work was mostly Elasticsearch and data infrastructure. It's shifted a lot since then. These days I'm building full AI pipelines: multi-agent workflows with LangGraph and CrewAI, RAG systems on Pinecone and Qdrant, voice AI agents that actually make phone calls (Vapi and ElevenLabs), and security automation that goes from alert ingestion to response without waiting for a human. Some of the more interesting things I've shipped: - An automated SOC workflow that triages SIEM/XDR alerts through L1/L2 AI agents and runs response playbooks - no analyst needed for first-response decisions - A full sales pipeline where AI handles outreach, runs live qualification calls, matches buyers to sellers, and closes deals with e-signatures. Humans only touch exception cases - An employee compliance agent that monitors Slack, has actual conversations with flagged employees, and escalates to an L2 agent trained on company policy via RAG - not just a flag-and-alert system - An AI-driven personalized search engine where results rank differently per user based on real behavioral signals, not a shared relevance score My infrastructure background is deep in Elasticsearch and OpenSearch - cluster design, multi-tenant architectures, ingestion pipelines, and performance work. I once took a 50M-document production cluster from visibly slow to sub-second and called it an 8x improvement. I've also built a full multi-tenant CSOC SaaS on AWS OpenSearch with Wazuh handling the security telemetry. Stack I work with day-to-day: Python (FastAPI, Flask), LangChain, LangGraph, CrewAI, n8n, Make, Supabase, Pinecone, Qdrant, Kafka, Docker, Kubernetes, AWS. LLMs: GPT-4o, Claude, Groq, Llama locally. Voice: Vapi, ElevenLabs, Twilio, Voiceflow. I stay until the thing works. Message me if you have a project that needs a real system.

I have 8 years of experience in Elasticsearch, Kibana, Logstash, and Beats. I provide Elasticsearch and Opensearch consultancy to companies serving in the fields of e-commerce, cybersecurity, and telecommunication. I have experience in the following areas: Elasticsearch and Opensearch - Installation & configuration on-prem and cloud - Tuning search & indexing speed - Performance optimization - Cost Optimization / Price Optimization - Full text search & NLP - Semantic search - Autocomplete features (search as you type) - Typo fix (spell corrector) - Suggesters (did you mean that ?) - Filtering & Ranking & Sorting - High availability & Fault tolerance & Resilience - Troubleshooting Elasticsearch Issue - Elasticsearch Architecture & Setup according to best practices - Query optimization - Aggregation, sub-aggregation, Highlight - Complex search queries (boolean) - Index mapping, template, multi-fields, rollover, index lifecycle, alias - Index settings, shard & replica count, root-balancing, synonym, analyzer, tokenizer - Best Practices - Log management and monitoring - SIEM Kibana - Business Intelligence - Creating dashboards that help the manager make decisions - Elasticsearch cluster monitoring - Multi tenancy Logstash & Beats - ETL process - Data Management - Data pipeline - Database and Data warehouse Migration / Synchronization - Log file import - Elasticsearch Monitoring - Grok / Mutate / Ruby

I specialize in building State-of-the-art AI-powered search engines.. Supporting companies optimize ranking and relevancy for higher find-ability leading to boosting conversion ands sales of their products. Additionally, I provide guidance on creating a superior search user experience (UX), ensuring that users have a seamless search journey through navigating your products. Working with Elasticsearch for over 8 years on various topics (Ranking, User query understanding and intent, NLP, Data-modeling, Scoring, Data Ingestion, built own Elasticsearch as a service, Monitoring) - 📚 Information Retrieval, Search engines & applications (Elasticsearch) - 🦾 AI & ML - 📱 Crafting customer-facing digital products. - 🔍 Data Analytics/Infrastructure, - 📦 Micro-services

Search Relevance & Product Analytics Specialist Algolia • Typesense • MeiliSearch • OpenSearch • Product Analytics • AI Retrieval I help SaaS, ecommerce, and AI companies improve search relevance, product discovery, and conversion performance through advanced search infrastructure and behavioral analytics. My work combines: * Search optimization * Product analytics * AI-powered retrieval * Personalization systems * Conversion optimization Search Expertise * Algolia optimization & relevance tuning * Typesense, MeiliSearch, ElasticSearch & OpenSearch implementation * Hybrid keyword + vector search * Semantic & neural search * InstantSearch & autocomplete experiences * Recommendation systems & personalization * No-result search optimization * Dynamic re-ranking using behavioral events Product Analytics & Growth * PostHog, Mixpanel, Amplitude & Rudderstack * Event tracking architecture * Funnel analysis & retention optimization * Behavioral segmentation * A/B testing & conversion analysis * Search analytics tied directly to engagement and revenue metrics AI Retrieval & Vector Search * RAG pipelines * Pinecone, Weaviate & pgvector * Semantic retrieval optimization * AI-powered discovery systems * Voice & conversational search Platforms & Integrations * Shopify * WooCommerce * React / Next.js * Flutter & FlutterFlow * Hygraph * Airtable Supporting stack includes React, Node.js, Python, PostgreSQL, Docker, AWS, and Kubernetes.

Unlock Lightning-Fast, Intelligent Search That Boosts User Engagement & Cuts Costs—With Proven 40% AI Accuracy Gains & 10ms Latency. As an Expert-Vetted Elasticsearch/OpenSearch specialist with 15+ years in data engineering, I've delivered 40+ successful projects on Upwork. Clients hire me to transform complex data challenges into revenue-driving solutions: from slashing batch processing from 126 hours to 2, to handling 75K+ concurrent users at 10ms latency, to reducing GenAI hallucinations by 40% via GraphRAG and knowledge graphs. 🟢 Just Message or Invite—If It's Feasible, I'll Guarantee Results. 🟢 How I Add Value to Your Project: AI & GenAI Mastery: Engineer agentic workflows, RAG/GraphRAG systems, and LLM integrations (OpenAI, HuggingFace, Bedrock) that ground answers in facts, improving search relevance and recommendation accuracy. Result: 40% fewer hallucinations, multilingual NLP for global scale (15+ languages). Elasticsearch/OpenSearch Optimization: Design high-availability clusters (on-prem, Kubernetes, cloud) for semantic/hybrid search, geo-spatial queries, autocomplete, and anomaly detection. Optimize costs, indexing speed, and security—managing 2PB+ data with fault-tolerant setups for SaaS multi-tenancy. Full ELK Stack & Integrations: Build Kibana dashboards for BI insights, Logstash ETL pipelines, and monitoring with Datadog/Prometheus. Migrate data warehouses, sync CDC pipelines, and integrate ML for inferences. Backend Prototyping: Rapid POC development in Java, Python, Node.js to validate ideas fast. Proven Client Success Stories: "Anil reduced our ES batch processing from 126h to 2h, stabilizing systems foundational to our business." (Enterprise client, $31K project) "Improved GenAI accuracy by 40% using GraphRAG—exceeded expectations." (SaaS platform, $9K project) "Handled 75K+ users at 10ms latency; a true difference-maker." (Web app integration, $6K project) See all 5-star reviews below for more: Clients praise my solution-oriented approach, clear communication, and commitment to quality. With federated clusters, cross-cluster replication and SIEM security, I've built resilient systems for e-commerce, finance and more. Let's discuss how I can scale your search/AI—message me today for a quick consultation!

I'm an AI agent developer and backend architect with 10+ years building production AI systems: autonomous agents, RAG pipelines, and automation that hold up under real users and real load. I've scaled platforms to 50M+ users and shipped AI for clients across the US, UK, and Australia. IIT Kanpur alumnus. I bring both the systems depth to make AI reliable and the product sense to make it useful. What I build: 1. AI agents and agent infrastructure. Autonomous agents, MCP servers, tool use, function calling, and multi-agent orchestration that run real workflows across ops, sales, and support. I also build the harness around them, state, retries, guardrails, and observability, so they hold up in production, not just in demos. 2. RAG pipelines that survive real load. Query embedding, parallel vector search, context assembly, and streaming LLM synthesis, with ETL ingestion, chunking, dedup, and PII guardrails built in. 3. Scalable, multi-tenant backend architecture. Node.js, TypeScript, NestJS, and Python microservices with multi-tenancy, governance, and security designed in from the start, over polyglot data layers: Postgres, MySQL, MongoDB, Redis, Elasticsearch, Neo4j, ClickHouse. 4. Workflow automation and integrations. End-to-end automations with n8n, Make, Zapier, and Temporal, wired into the tools teams already use: Slack, Notion, WhatsApp, ClickUp, Telegram, and more. Selected work: - Scaled a creator-economy platform to 50M+ users on AWS EKS and Cloudflare Workers, including payments infra with Stripe Connect, Apple IAP, and Google Play Billing. - Built AI agents and MCP servers for an AI-native business platform handling finance, sales, and support workflows. - Re-architected an autonomous AI worker platform for multi-tenancy, scalability, governance, and security. - Designed a conversational RAG copilot on PostgreSQL + pgvector for project management and admin tasks via natural language. - Integrated Facebook, Google, Instagram, and TikTok ad APIs across 800+ store locations for local inventory ads and ROI tracking. Core stack: Models and frameworks: GPT-4o, Claude, Gemini, LangChain, LlamaIndex, AutoGen, CrewAI, LangGraph, LangSmith, Semantic Kernel, DSPy. Agent infrastructure: MCP servers, function calling, tool use, multi-agent orchestration, OpenClaw, Hermes, LangServe, Modal, Replicate. Vectors and memory: Pinecone, pgvector, Weaviate, Chroma, Redis. ML and DL: TensorFlow, PyTorch, Hugging Face, Scikit-learn. Backend: Node.js, TypeScript, NestJS, Python, FastAPI, GraphQL, WebSockets, WebRTC, RabbitMQ. Data: Postgres, MySQL, MongoDB, Redis, Elasticsearch, Neo4j, ClickHouse, Firebase. Integrations: Slack, Notion, WhatsApp, ClickUp, Telegram, Twilio, Akamai, Rosette, Facebook Graph, Stripe, and marketing APIs across Facebook, Google, TikTok, Twitter, and Dropbox. Cloud: AWS (Lambda, RDS, SQS, OpenSearch, Neptune, S3, ElastiCache, Comprehend, Rekognition), GCP (Firestore, Cloud Functions). If you need someone who can take an AI idea from prototype to a system that survives real users and real load, let's talk. I reply fast and ship faster.

Got a project that needs AI baked in, not bolted on? Or just need Laravel/WordPress work done by someone who actually knows what they're doing? I've been building web apps for 11+ years, custom Laravel backends, WordPress platforms, WooCommerce stores, the whole stack. Lately, a big part of my work is AI and automation: OpenAI/Claude integrations, chatbots that actually understand context using RAG, workflow automation with n8n, API layers that tie your tools together so things just work. Some things I've worked recently: - A marketing platform with a live dashboard showing campaign performance for clients with AI insights - A healthcare portal used by 4,000+ employees for checkups, doctor communication, and document uploads - A real estate platform with maps, data viz, and API integration with 6,000+ properties in the DB - WooCommerce store with a fully custom Vue.js product builder - An internal invoicing platform for a publishing company I keep things simple on the communication side, no hour-long calls for things that are clear in a message. Just clean code, honest timelines, and quick replies. If something breaks, I'm on it. If I don't know something, I'll say so. Top 3% on Upwork, $600K+ earned, 204 contracts done. Click "Invite to Job" if you want to talk. ===================== Keywords: Laravel, PHP, WordPress, WooCommerce, WooCommerce Subscriptions, JavaScript, Vue.js, Full Stack Development, AI Integration, Chatbot Development, OpenAI, OpenAI API, ChatGPT, n8n, Workflow Automation, REST API, API Integration, Stripe, PayPal, HubSpot, AWS, Docker, ACF Pro, Gutenberg, Digital Ocean, Elasticsearch, Redis, MongoDB, WebSockets, Queues, Laravel Forge, Git, GitHub, Jira, Asana

If your looking for the best, hiring a top 1% consultant = saved time and money. I'm your guy I help companies with valuable datasets organize and simplify their data to bring value without the stress of managing the implementation. 10 years of experience to handle the entire process with minimal hand holding to bring you maximal value in a shortest time. Observability and data analysis Cluster architecture, mappings, data strategies, ingest pipelines. I work to optimize all of these so that the data can start providing value ASAP. Search RAG, semantic search, lexical search, hybrid, ANN, KNN, chatbot, vector search, recommendation engines, analyzers, suggestions and search as you type are all important to curating a product your customers can't resist using. Offload the mental stress of sorting out the nitty gritty details of implementation and let me help create your data system for you. Clients often refer to me as their “cheat code” because a brief call with me can replace hours of frustrating trial & error and research. I have a simple goal: 1) To fully understand your needs, 2) Eliminate any stress or confusion, and 3) Deliver precisely what you’re looking for—taking care of all the details for you. I know how frustrating it can be to hire freelancers who complicate things further, communicate poorly, surprise you with unexpected costs, and require so much oversight that it feels easier to handle the work yourself. Types of work I’ve done: Search Engine Development: Built and optimized high-performance search engines with a focus on user experience, achieving sub-500ms response times. A good search engine prioritizes user experience above all. The user needs to 1) get what they want (relevance), and 2) as fast as you can give it to them <500ms (latency), it's that simple. Full ELK Stack Implementations: Designed and deployed ELK stacks for diverse industries, including healthcare and renewable energy, handling everything from parsing error logs to integrating with third-party tools like Jira and Twitter. Custom Dashboard Creation: Developed visually appealing and functional dashboards for data visualization, enhancing team productivity and decision-making. Automation and Optimization: Automated cluster installations and optimized Logstash/filebeat/ingest pipelines configurations for efficient data processing and error handling. I will explain things in layman's terms and not fill an explanation of how something works with technical jargon. I will be clear with my expectations and happy to explain how things work so you can do it yourself. Let's work on your project together so that you can get what you want out of your data. Additional Competencies: API integration with ELK: Facebook, Google Analytics, Twitter, etc... Automation of ELK: Bash and Ansible External Database Syncing with ELK: SQL, MongoDB Misc: Readonly Rest, Own_home, Searchguard, Graphite, alerting, siem, watcher, docker, AWS, OpenSearch Filebeat, metricbeat, packetbeat, Vega, RAG, LLM, AI augmented search, index templates,