A named expert, visible credentials, and a clear path to working together, not an anonymous AI staffing profile.
Jaimin Patel is a Lead AI Engineer and Team Lead, focused on delivering production-grade backend, computer vision, and automation solutions across healthcare, finance, compliance, education, and e-commerce. He has experience with Claude-Powered AI Solutions, Python, Flask, FastAPI, computer vision, LLM applications, and AI integrations, emphasizing scalable, reliable automation and measurable operational efficiency.
Anthropic courses
Expert collaboration
Initial response target
What you can hire this architect for:Â Claude API applications, RAG knowledge assistants, MCP-connected tools, Claude Code implementation, agent and subagent orchestration, workflow automation, and enterprise integrations.
A named expert, visible credentials, and a clear path to working together, not an anonymous AI staffing profile.
Yash Patel is a Lead AI Engineer, focused on building and deploying production-grade Generative AI systems, Agentic AI workflows, multi-tenant SaaS architectures, LLM applications, and scalable backend systems. He has experience with Claude-Powered AI Solutions, MCP integrations, CRM integrations, AWS serverless ecosystems, and RAG pipelines, emphasizing performance, scalability, and cost optimization.
Anthropic courses
Expert collaboration
Initial response target
What you can hire this architect for:Â Claude API applications, RAG knowledge assistants, MCP-connected tools, Claude Code implementation, agent and subagent orchestration, workflow automation, and enterprise integrations.
A named expert, visible credentials, and a clear path to working together, not an anonymous AI staffing profile.
Yashish Shah is a Lead AI Engineer, focused on delivering production-grade AI, backend, and automation solutions across healthcare, finance, compliance, education, and e-commerce. He has experience with Claude-Powered AI Solutions, Python, Django REST Framework, n8n, LLM applications, and AI Integrations, emphasizing scalable, reliable automation and measurable operational efficiency.
Anthropic courses
Expert collaboration
Initial response target
What you can hire this architect for:Â Claude API applications, RAG knowledge assistants, MCP-connected tools, Claude Code implementation, agent and subagent orchestration, workflow automation, and enterprise integrations.
A named expert, visible credentials, and a clear path to working together, not an anonymous AI staffing profile.
Chaitali Patel is a Lead AI Engineer focused on building and deploying production-grade Generative AI and Agentic AI solutions. She works on designing AI-powered systems that automate complex business processes, connect with existing enterprise systems, and handle real-world unstructured data and workflows. Her work emphasizes reliability, scalability, and practical business automation, with a focus on delivering solutions that can be used effectively in production environments.
Anthropic courses
Expert collaboration
Initial response target
What you can hire this architect for: Claude API applications, Claude Computer Use agents, document intelligence, RAG knowledge assistants, MCP tool integrations, browser automation, agentic workflows, and enterprise AI automation.
A named expert, visible credentials, and a clear path to working together, not an anonymous AI staffing profile.
Jay Patel is a Senior AI Engineer at Pragnakalp, focused on building scalable, production-grade Healthcare AI platforms for document intelligence, and AI-Powered SaaS architecture. With experience in Claude-Powered AI Solutions, agentic workflows alongside Python, Django REST Framework, Next.js/React, Azure, OpenAI and HIPAA-ready solution architecture.
Anthropic courses
Expert collaboration
Initial response target
What you can hire this architect for:Â Claude API applications, RAG knowledge assistants, MCP-connected tools, Claude Code implementation, agent and subagent orchestration, workflow automation, and enterprise integrations.
A named expert, visible credentials, and a clear path to working together, not an anonymous AI staffing profile.
Neel Patel is a Senior AI Engineer at Pragnakalp, specializing in building scalable, production-ready AI solutions for enterprise use cases. Her expertise spans Claude Code, the Claude Agent SDK, Model Context Protocols (MCPs), LLMs, multi-agent orchestration, Voice AI, and intelligent automation workflows.
Anthropic courses
Expert collaboration
Initial response target
What you can hire this architect for:Â Claude API applications, RAG knowledge assistants, MCP-connected tools, Claude Code implementation, agent and subagent orchestration, workflow automation, and enterprise integrations.
A named expert, visible credentials, and a clear path to working together, not an anonymous AI staffing profile.
Harvi Patel is a Senior AI Engineer at Pragnakalp, focused on building scalable AI solutions for enterprise use cases. With experience in Claude Code, the Claude Agent SDK, MCPs, LLMs, multi-agent orchestration, Voice AI, and automation workflows.
Anthropic courses
Expert collaboration
Initial response target
What you can hire this architect for:Â Claude API applications, RAG knowledge assistants, MCP-connected tools, Claude Code implementation, agent and subagent orchestration, workflow automation, and enterprise integrations.
A named expert, visible credentials, and a clear path to working together, not an anonymous AI staffing profile.
Ayush Patel is an AI Engineer at Pragnakalp, focused on building production-ready Generative AI solutions, LLM-powered applications, chatbots, and intelligent automation systems. He has experience implementing AI-powered features, integrating LLMs for content and analysis generation, and developing AI-driven workflows using Claude, Python, Flask, and other modern AI technologies.
Anthropic courses
Expert collaboration
Initial response target
What you can hire this architect for:Â Claude API applications, RAG knowledge assistants, MCP-connected tools, Claude Code implementation, agent and subagent orchestration, workflow automation, and enterprise integrations.
A named expert, visible credentials, and a clear path to working together, not an anonymous AI staffing profile.
Nikunj Patel is an AI Engineer, focused on delivering production-grade AI, backend, and automation solutions for AI-powered leadership analytics, healthcare and finance. He has experience with Claude-Powered AI Solutions, Python, Flask, Elasticsearch, MCPs, LLMs, and multi-agent orchestration, emphasizing scalable, reliable automation and measurable operational efficiency.
Anthropic courses
Expert collaboration
Initial response target
What you can hire this architect for:Â Claude API applications, RAG knowledge assistants, MCP-connected tools, Claude Code implementation, agent and subagent orchestration, workflow automation, and enterprise integrations.
Claude is Anthropic’s family of large language models, known for strong reasoning, long-context understanding, and a safety-first design that enterprises trust with sensitive data.
But the model is only half the story. Getting real value means choosing the right model for the job, engineering prompts and skills, wiring Claude into your systems, and controlling cost at scale. That is exactly where our developers work every day.
Context windows for whole documents and codebases
Native tool and system connections via Model Context Protocol
Trusted in privacy-sensitive healthcare and finance workflows
Web search, web fetch, and multi-step autonomous loops
Anyone can call an API. A certified developer knows the features that decide whether your project is fast, accurate, and affordable in production.
Credentialed through Anthropic's own training, our developers apply proven patterns instead of guessing their way through the docs.
Prompt caching, batch processing, and structured outputs are not buzzwords to us. Used well, they cut cost and latency dramatically.
We build for evaluation, monitoring, and maintenance from day one, so your Claude system stays accurate long after launch.
End-to-end delivery across the Claude ecosystem, tailored to your product and your data.
Connect Claude to your app, CRM, database, or internal tools with clean, maintainable, production-ready code.
Retrieval systems grounded in your knowledge, with source attribution and structured outputs you can trust and render.
Autonomous agents that use web search, web fetch, and MCP tools to complete real multi-step tasks reliably.
Extract entities, classify line items, and structure PDFs, emails, and scans with Claude's vision and reasoning.
Encode your domain rules as reusable Agent Skills and add cross-session Memory for consistent, improving output.
Prompt caching and batch processing to cut re-ingestion cost and latency, with batch runs reducing spend significantly.
Three production systems, with the exact Claude features that made each one work.
Two Claude Skills, Job Search and Job Ranking, work together inside Claude Code. Claude in Chrome and Computer Use navigate real job platforms, extract structured listings, and Claude Sonnet ranks every opportunity against the user’s requirements.
We ingest a full Oracle schema, embed it with Voyage Code 2, and answer natural-language questions with Claude Sonnet. A second pipeline turns schema objects into Mermaid ER diagrams that stay in sync with the live database.
Procurement quotes arrive as PDFs, email text, or URLs. Claude Opus extracts vendor, part number, condition code, and tagged-by, then classifies every line item. Agent Skills encode domain rules and the Memory tool keeps context across sessions.
Senior engineers who work with Claude every day, not occasional dabblers.
Seamless collaboration across every time zone your team works in.
Kick off immediately with architects who are ready to build now.
A trial period with a fast replacement if the fit is not perfect.
Clear visibility at every step of your Claude development journey.
Maximum value for your budget, with caching and batch built in.
Strong relationships built for continuous AI innovation.
A track record of clients who come back for the next build.
Design, build, deploy, and maintain, all under one roof.
Product intelligence, support automation, and personalized shopping experiences.
Safe document analysis and knowledge assistants for privacy-sensitive data.
Report generation, risk analysis, and secure, compliant data handling.
Quote extraction, line-item classification, and contract intelligence.
Structured data collection and enrichment across the web at scale.
Claude features embedded natively into your product for real user value.
Claude can power chatbots and assistants, extract and structure data from documents, run autonomous multi-step agents, build RAG systems over your knowledge, and automate content and analysis, all with a safety-first design enterprises trust.
Certified architects know the specific features, prompt caching, batch processing, structured outputs, extended thinking, that decide whether your system is fast, accurate, and affordable in production. That expertise is the difference between a demo and a dependable product.
Claude is known for strong reasoning, long-context handling, and a safety-first approach that makes it a common choice for privacy-sensitive work. The right model depends on your use case, and we help you choose rather than assume.
Yes. We connect Claude to your CRM, databases, internal tools, and third-party services, including through the Model Context Protocol, so it fits your current stack instead of replacing it.
We use prompt caching to avoid re-processing large, repeated context, and batch processing for asynchronous workloads, which reduces spend significantly. We also right-size the model to the task rather than defaulting to the largest one.
Yes. On delivery you receive full ownership of the code and the solution built for you.
It depends on scope and complexity. After a short discovery call we give you a transparent estimate for both timeline and cost so there are no surprises.
