Agentic Workflows Development using LangChain

@Microlent

Moving from LangChain experiments to stable agentic workflows requires more than just agent orchestration, it requires a solid strategy for governance and guardrails. We recently built a Python Deterministic Scoring Engine to handle high-stakes data decisions with absolute accuracy and auditability. This system ensures that outcomes remain consistent even as data scales, which is the missing piece for most production AI. You can view the details here: https://www.freelancer.com/portfolio-items/11337466-python-deterministic-scoring-engine I can help your team bridge the gap between initial POCs and deployments that actually stay resilient in the wild. My focus is on setting up LangGraph for reliable state management and integrating PySpark pipelines so your vector search stays efficient as your document processing grows. I usually start by looking at the evaluation layer first, since you can't scale what you can't measure. I can put together a quick production-grade LLMOps pipeline draft so you can see the approach first. Happy to jump on a quick call when you're ready. Best, Rajesh

@kamran2012

I can help with this, I will build your agentic workflows using LangGraph — multi-step agents for data validation, document processing, and reporting — along with RAG pipelines, prompt orchestration, and the supporting data infrastructure. For agent reliability, I will implement a supervisor-worker pattern in LangGraph where a routing agent delegates tasks to specialized sub-agents, each with defined tool access and fallback logic. This keeps workflows modular and debuggable — far easier to monitor and scale than a single monolithic chain. Questions: 1) Which LLM providers are you targeting primarily — OpenAI, Gemini, or open-source models like LLaMA via local inference? 2) What is your current cloud environment and vector store setup for the RAG components? Ready to start whenever you are. Kamran

@Srashtasoft

Hello, I’m an experienced AI/ML Engineer specializing in Agentic AI, GenAI applications, and LLMOps. I have built production-grade solutions using LangChain, LangGraph, GPT, Gemini, and open-source LLMs to automate complex business workflows. My experience includes developing autonomous agents for document processing, data validation, reporting, and domain-specific decision workflows. I have implemented RAG architectures with vector databases, prompt orchestration, retrieval optimization, and model evaluation frameworks to deliver accurate and reliable AI experiences. I can contribute across the complete AI lifecycle, including: • Multi-agent workflow design using LangChain/LangGraph • GenAI applications with GPT, Gemini, and LLaMA • RAG, vector search, embeddings, and evaluation pipelines • Python and PySpark data engineering • API/SDK development and enterprise integrations • CI/CD for AI systems, monitoring, guardrails, and governance • MLOps/LLMOps best practices for scalable deployments • Cloud and hybrid optimization for performance and resilience I work closely with product, analytics, and engineering teams to translate business requirements into production-ready AI solutions while supporting architecture reviews and knowledge sharing. I would welcome the opportunity to discuss your use cases and demonstrate how I can help accelerate your GenAI initiatives with robust, enterprise-grade implementations. Best regards, Jemin Sagar

@pkundu25

Hi there,I am an experienced AI Developer specializing in building production-grade agentic workflows and advanced GenAI applications. Your project aligns perfectly with my deep expertise in LangChain, LangGraph, and RAG architectures. Key Relevant Expertise: • Document Segmentation & Processing: Proven track record of breaking down complex, unstructured documents into logical, context-aware segments. I implement advanced chunking strategies that preserve semantic meaning, which is critical for downstream LLM processing. • Semantic Search & RAG: Built highly accurate semantic search engines using vector databases and models like GPT, Gemini, and LLaMA. I optimize search retrieval via hybrid search, re-ranking, and dynamic prompt orchestration. • Agentic Workflows: Expert in designing autonomous, resilient multi-agent systems using LangGraph. I develop stateful agents with built-in guardrails for automated data validation, reporting, and complex domain workflows. • Production & MLOps: Experienced in productionizing POCs into scalable distributed pipelines (Python/PySpark). I build secure APIs, implement robust CI/CD for LLMs, and set up continuous monitoring and evaluation. I am ready to collaborate with your product and data teams to deliver high-performance, governed AI solutions. Let’s connect to discuss your architecture and pipeline requirements in detail.

@shadabkhan92

With my comprehensive skill set and experience in AI Development, Mobile App Development, and Python, I am confident that I can deliver exceptional results for your agentic workflows project using LangChain. My name is MOHD SADAB, and I lead a team that specializes in turning innovative ideas into fully functional, production-grade infrastructure. Our unique approach combines the power of odoo ERP, IoT, and web/mobile application development to bring AI into everyday operations effectively. What truly sets us apart from others is our ability to execute where others may struggle. We work across multiple front-end frameworks like React and Flutter, back-end environments such as Django and Node.js and have unique proficiency in AWS, GCP, Azure providing a versatile post-development experience across cloud/hybrid domains. As you mentioned you need ‘AI that really works where others can't'; our proficiency of deploying AI models on the edge where the infrastructural insights are of utmost requirement can be the element to surpassing your target goals. Throughout our collaborations with diverse teams - analytics, product, engineering- we've fostered a deep appreciation for iterative development cycles and have honed the skills of adapting accordingly. This ability to undertake feedback positively along with our knowledge-sharing culture has allowed us to enhance GenAI capability trifold in each project execution; an added value we bring to exceed customer expectations.

@jarviskb

Hi, I’d be excited to contribute to this role focused on Agentic AI, GenAI application engineering, data platforms, and LLMOps. I have strong hands-on experience building AI agents, RAG systems, document intelligence workflows, reporting automation, data validation agents, and production-ready GenAI applications using LangChain, LangGraph, OpenAI/GPT, Gemini, LLaMA, Claude, Python, FastAPI, vector databases, and cloud services. For this role, I can help design and build autonomous and semi-autonomous agentic workflows for data validation, document processing, analytics/reporting, and business-domain automation. I have experience with prompt orchestration, tool-calling agents, structured outputs, retrieval pipelines, vector search, reranking, evaluation frameworks, and guardrails to make AI systems reliable in production. On the platform side, I can contribute to APIs, SDKs, integration layers, backend services, and scalable data pipelines using Python and PySpark. I am comfortable working across cloud or hybrid environments, optimizing for performance, scalability, monitoring, and maintainability. I also understand the importance of LLMOps/MLOps, including CI/CD, testing, deployment, evaluation, observability, governance, and reusable GenAI frameworks. I can work closely with product, analytics, data science, and engineering teams to turn POCs into production systems and support architecture reviews, iterative delivery, and internal GenAI capability building.

@Jennycreation

With a team of developers boasting over 17 years of comprehensive experience in web, window and Android development, my service is specialized, skilled, and reliable – every time. While my profile may not explicitly align with your requested skills for GenAI, the cross-functional nature of my expertise serves as an invaluable addition to your project. My expertise spans across different programming languages including Java and Python, and this range ensures a holistic understanding that ultimately enhances the quality of my work. Additionally, I've excelled in building distributed data pipelines (Python, PySpark), developing APIs and SDKs for creating AI-powered applications, and optimizing systems for performance and scalability in various environments. This makes me well-equipped to tackle the challenges of deploying scalable and resilient agent pipelines that you mentioned in your project description. You can be confident in my ability to deliver top-tier results while strictly adhering to deadlines. As a testament to my commitment to client satisfaction, I've been working around the clock for more than 15 years to ensure excellent delivery at the fairest prices.

@techsty2014

Hey, We will build your agentic workflow system using LangGraph, with autonomous agents for data validation, reporting, and document processing. For the agent orchestration, we will structure each agent as a node in a LangGraph state machine with typed state transitions. This makes debugging predictable and lets us add guardrails (token limits, output validation) at each node rather than only at the final output. A couple of quick things to confirm: 1) Which LLM providers are in scope (GPT, Gemini, LLaMA), and is there a preferred hosting setup for open models? 2) Do you have existing data pipelines we will integrate with, or are those part of this build? The number quoted here is a starting estimate. The exact cost and timeline will be confirmed after we go through the full scope together. Looking forward to discussing further. Best regards, Faizan

@KarthikTechCon

Hello, I'm Karthik, with 15+ years of experience in enterprise software, AI/ML, cloud architecture, and data engineering. Our team has hands-on expertise building Agentic AI solutions using LangChain, LangGraph, CrewAI, OpenAI GPT, Gemini, Llama, and AWS Bedrock. We can help design and implement autonomous agent workflows for document processing, data validation, reporting, and domain-specific business automation. ✔ LangChain & LangGraph agent orchestration ✔ Multi-agent systems with tool calling and workflow automation ✔ RAG pipelines, vector databases, and semantic search ✔ GPT, Gemini, Llama, Claude, and Bedrock integrations ✔ Python, FastAPI, PySpark, and distributed data pipelines ✔ API/SDK development and enterprise integrations ✔ LLMOps, monitoring, evaluation, guardrails, and governance ✔ CI/CD deployment on AWS, Azure, and GCP Our approach focuses on building production-ready, scalable, and observable AI systems with strong security, monitoring, and performance optimization. We have experience transforming GenAI POCs into enterprise-grade solutions that deliver measurable business value. I would be happy to discuss your use case and propose the optimal architecture and implementation roadmap. Best Regards, Karthik 15+ Years Experience | AI, Data Engineering & Cloud Solutions

@jaroslavcaprata

Hi, there. I have experience building AI-powered applications using LangChain, LangGraph, OpenAI, Gemini, vector databases, and RAG architectures. My recent work includes multi-agent workflows for document processing, knowledge retrieval, validation pipelines, and enterprise automation systems. I am comfortable working across the full stack, from agent orchestration and prompt engineering to API development and cloud deployment. For this role, I can design and implement scalable agentic workflows with monitoring, evaluation, and guardrails built in from the start. Whether it's autonomous data validation, reporting agents, document intelligence, or domain-specific workflows, I focus on creating modular systems that are reliable, traceable, and easy to maintain. I also have experience integrating LLM applications with data pipelines, external APIs, and enterprise platforms. My development approach combines strong software engineering practices with practical AI architecture. I prioritize performance, observability, and production readiness while ensuring solutions remain flexible as requirements evolve. I’d be excited to contribute to both the engineering and architectural aspects of your GenAI initiatives. Thanks.

@NEHABHAT92

With almost a decade of experience in mobile app and web development, I have had the privilege of working on diverse projects that span across multiple industries. Throughout these experiences, I have consistently honed my skills in Python - a crucial technology in your project. Moreover, given that I have built distributed data pipelines using Python before, including working with libraries such as PySpark, executing this component of your project will not be a challenge for me. Additionally, having worked intently on Mobile App Development and API integration, I am well-versed in optimizing systems for performance and scalability across different environments. This is an essential plus for your project since we are looking to develop scalable and resilient agent pipelines with monitoring and evaluation leveraging frameworks like LangChain/LangGraph. Lastly, while I may not have extensive experience with AGI technologies specifically like GPT and Gemini, my proficiency in the field of AI Development combined with my quick learning ability equips me to effectively partner with data scientists to productionize proof-of-concepts (POCs). Indeed, I'm enthusiastic about the opportunity to collaborate with your team on this transformative project and look forward to exceeding your expectations with a high-quality output that aligns seamlessly with your vision.

@DigitalNightOwl8

Hi , Good afternoon! I’ve carefully checked your requirements and really interested in this job. I’m full stack node.js developer working at large-scale apps as a lead developer with U.S. and European teams. I’m offering best quality and highest performance at lowest price. I can complete your project on time and your will experience great satisfaction with me. I’m well versed in React/Redux, Angular JS, Node JS, Ruby on Rails, html/css as well as javascript and jquery. I have rich experienced in MLOps, Python, Java, Mobile App Development, AI Development, LangChain, AI Model Development and Google App Engine. For more information about me, please refer to my portfolios. I’m ready to discuss your project and start immediately. Looking forward to hearing you back and discussing all details.. Always happy to hear from you

@zeeshanmcp12

I specialize in developing agentic workflows using LangChain and LangGraph to create autonomous agents for data validation, reporting, and document processing. With experience in deploying scalable agent pipelines and GenAI applications utilizing models like GPT and Gemini, I am well-equipped to implement RAG, vector search, and prompt orchestration. My expertise extends to building distributed data pipelines, developing APIs, and optimizing systems for performance and scalability across cloud environments. I have a proven track record of contributing to CI/CD workflows for AI models and collaborating with cross-functional teams to deliver AI solutions effectively. Let's work together to enhance your AI capabilities and drive impactful results. https://www.freelancer.com/portfolio-items/11387648-ai-lead-agent-for-online-academy https://www.freelancer.com/portfolio-items/11387726-personal-ai-os-for-tech-founder Thank you.

@coretus

Agentic workflows need more than prompts. They need solid orchestration, validation, monitoring, and a production-ready architecture that can scale safely. That is exactly where I can help. Relevant fit: - LangChain and LangGraph based agent workflows. - AI model development, MLOps, and scalable software architecture. - Python, Java, and backend integration for data and platform engineering. - GenAI applications with RAG, prompt orchestration, and evaluation. Plan: 1. Design the agent architecture for data validation, reporting, document processing, and domain workflows. 2. Build reusable agent pipelines with guardrails, monitoring, and evaluation hooks. 3. Implement integrations, APIs, and scalable deployment patterns for resilient execution. 4. Work iteratively with your team to refine POCs into production-ready components. Pricing: My bid is 56,000 INR. This stays within your budget and reflects the scope of autonomous workflows, GenAI engineering, and deployment hardening without overcharging for standard boilerplate. If you want, I can start with a focused architecture review and a first workflow prototype, then expand in milestones. https://www.freelancer.com/u/coretus Best regards, Coretus Technologies

@KrisuTechkul

With my extensive experience in AI development coupled with a keen understanding of LangChain and other frameworks, I am excellently positioned to create agentic workflows for your project. Throughout my career, I have built autonomous agents specializing in data validation, reporting, document processing, and domain workflows - all the aspects your project requires. What distinguishes me further is my ability to deploy scalable and resilient agent pipelines with robust monitoring and evaluation capabilities. I understand that efficiency and reliability are top priorities while handling large amounts of data in complex systems, which is why I emphasize on these aspects during deployment. Needless to say, my skills go far beyond just agentic workflows. My proficiency in GenAI application engineering will enable me to develop intelligent applications using state-of-the-art models such as GPT, Gemini, and LLaMA that can significantly boost your processes. Additionally, my expertise in building distributed data pipelines (Python, PySpark), developing APIs, SDKs, and integration layers for AI-powered apps will ensure a seamless integration of the workflows into your existing systems. Moreover, I have spent a considerable portion of my career optimizing systems for performance and scalability across cloud/hybrid environments. This skill will prove invaluable when deploying your solution at scale.

@TechWagger2026

As a well-rounded freelance technologist, I possess comprehensive knowledge and ample experience with MLOps, GenAI, Data Engineering ecosystems, setting me apart. With profound expertise in AI Development and data-driven solutions, I offer strategic insights to translate your concept into a scalable, value-adding reality. My proficiency in LangChain using Python aligns excellently with your project's requirements. Over the course of my 14+-year career, I have consistently delivered top-notch projects that optimize system performance across cloud/hybrid environments leveraging Distributed data pipelines (Python & PySpark) and developing APIs and SDKs for AI-powered applications, demonstrating my ability to juggle complexity whilst maintaining efficiency. Additionally, my sleek fluency with widely adopted Microsoft tech as ASP.NET and Azure SQL Server and extensive hands-on skill set in various data-storage technologies like SQL, MongoDB makes me an ideal fit for a task that requires collaboration and effective communication skills to deliver AI solutions at their best. I thrive on blending technical finesse with business objectives to design workflows that not only automate processes but also support knowledge-sharing & internal growth. Let me assure you, partnering with me would be like having an innovation-oriented teammate always seeking ways to help your business grow, as we move dynamically into the Era of Artificial Intelligence!

@manoval09

Hi, I understand you need agentic workflows that can reliably orchestrate multiple agents with tool-use capabilities and managed state—that's where most teams hit friction trying to scale beyond simple chains. I've built several production LangChain and LangGraph systems, and the difference is almost always in architecture: how agents hand off tasks, maintain context across steps, and handle tool failures gracefully. I'd structure your workflow using LangGraph's state persistence layer—it's the right choice here because it gives you deterministic replay, clear fault boundaries, and clean separation between agent logic and orchestration. I'd build each agent as a composable node with explicit inputs/outputs, using LangChain's tool-calling patterns for reliable integrations. All code goes to Git with clear test coverage for agent behaviors. First 24 hours: I'll map the full agent graph—what each agent does, how they communicate, which tools they need, and error recovery points. This gives us a clear blueprint before implementation. What's your intended use case for the agents, and do you have existing APIs they need to integrate with? Best regards, Val

@sgwtechnology

I am an AI/ML Engineer with experience building GenAI applications, agentic workflows, and scalable data platforms. I have worked with LangChain, LangGraph, GPT-based systems, RAG pipelines, vector databases, prompt orchestration, and LLM evaluation. My background includes developing autonomous agents for document processing, validation, reporting, and business workflows, as well as building APIs, distributed data pipelines, and cloud-native AI solutions. I am experienced in MLOps/LLMOps practices, including CI/CD, monitoring, governance, and model deployment. I enjoy collaborating with cross-functional teams to transform AI concepts and POCs into reliable, production-ready solutions that deliver measurable business value.

@iterativeTech

With my diverse technical expertise and hands-on experience in Agile System Development Life Cycle (SDLC), I believe I check all the boxes required for your langChain project. My robust understanding of similar frameworks like GPT, Gemini, LlAMA coupled with my proficiency in LangChain will empower me to build thoughtful, autonomous agent workflows that validate and process data more efficiently using AI. Moreover, I have designed and deployed several agentic workflows in the past which allows me to streamline complex document processing pipelines while ensuring the highest levels of accuracy and domain relevance. Deploying scalable and resilient agent pipelines with advanced monitoring and evaluation systems is my forte. Thus, I will ensure your workflow functions optimally, as expected. Furthermore, my exposure to Data & Platform Engineering along with MLOps/LLMOps strengthens my candidature. I can analyze and optimize system performance and scalability across hybrid/cloud environments to deliver a future-proof project pushing the boundaries of AI deployment. In addition, my ability to work in conjunction with data scientists for model productionization will drive maximum ROI-bedrooming resulted from successful POCs. Let's convert ideas to reality by shaking hands on this project for an exceptional transformation!