Hands-On Agentic AI Engineering & Consulting
Production Agentic AI systems — multi-agent supervisors, validators, and initiators that comprehend, decide, and execute real business work, with guardrails, observability, and ethical-AI safeguards that make them trustworthy at scale.
Founded by Surendra Kashyap · Registered in Illinois, USA · Serving Austin · Chicago · Remote
End-to-end design and hands-on build of multi-agent systems: supervisor orchestration, skill-based delegation, validator/initiator pipelines, persistence, and observability. Production-grade from day one.
Take an existing AI POC to production: prompt engineering, multi-pass continuation, structured extraction, ethical-AI safeguards, feature-flag-first delivery, and LLM-aware regression suites.
Help your engineering team adopt Claude Code, GitHub Copilot, and frontier LLMs as collaborative peers — not as prompt-and-walk-away generators. Architectural intent first, prompts second.
Cloud-native modernization on AWS (EKS/ECS, Kubernetes, Terraform, Spinnaker, Harness). Java / Python / Node.js polyglot capability. Refactor legacy to scalable, observable services.
From problem framing to production operating model. We don't hand off at the demo.
Code is the deliverable. We make decisions, write code, and stay close to the outcome.
Success is measured in business results: cognitive burden removed, transactions completed, time given back.
Compliance-aware prompts, deterministic validators, audit trails. Trust is engineered, not bolted on.
2–4 weeks
Discovery + working POC. We frame the problem, prototype the agent architecture, and prove or disprove feasibility with real data.
Outcome: A clear go/no-go and a defensible plan.
8–16 weeks
Whiteboard to production system. We design, code, harden, and ship the agentic system end-to-end.
Outcome: A deployed system handling real traffic with full observability.
3–6 months
Hands-on architect inside your team. We own the AI architecture, code daily alongside your engineers, and hand off a system your team can extend.
Outcome: Capability transfer, not dependency.
Ongoing
AI-augmented engineering practice for an existing team. We help your engineers adopt agentic coding tools and build their own production AI muscle.
Outcome: Team-level uplift.
years of hands-on software engineering across financial services, platform engineering, and enterprise systems (J.P. Morgan Chase, TD Ameritrade, Morgan Stanley, Invesco, GE).
years in production Generative AI and LLM integration.
years architecting Agentic AI systems in production financial services — sole architect, coder, and operator of a multi-agent Supervisory AI Agent at J.P. Morgan Chase.
Lead AI Engineer · Hands-On Agentic Coder · End-to-End Owner
AWS Certified Solutions Architect (Associate), Sun Certified Java Developer, Machine Learning. Polyglot across Python, Java, Node.js, and modern frontend. Mentor and co-learner; leads an informal AI learning community. Based in Lombard, Illinois.
Whether you need a production AI agent, a modernized platform, or a team that thinks in outcomes — we're ready to talk.