How is this different from building on ChatGPT or Claude directly?

Raw GPT is a reasoning component. Production agents need state machines, tool schemas, retries, guardrails, memory, observability, and human-in-the-loop escalation. That's the 90% of work that decides whether an agent ships or rots in a demo. We build that layer — you own it.

What happens if the underlying LLM (GPT-5, Claude 4) ships and breaks my agent?

Model-agnostic by design. Every agent has an eval suite — when a new model ships we re-run evals, swap if better, roll back if worse. Same LangGraph code runs across GPT-5.5, Claude Opus 4.8, Google models, Llama. No rewrites, no vendor lock-in.

Can agents actually be trusted in production without hallucinations?

Yes, when architected right. Grounded retrieval with forced citations, typed tool outputs, output validation schemas, human-in-the-loop on high-stakes decisions, and eval suites that fail the build if hallucination rate exceeds your contracted threshold.

How do you measure agent success — not impressions, real outcomes?

Contracted task-success rate (did the agent complete the goal?). Plus latency p95, cost per run, tool error rate, human-override rate, hallucination rate. Dashboards in LangSmith or Langfuse. You see every trace. If we miss the benchmarks we iterate free.

On-prem or private LLM for regulated data?

Yes. Llama, Mistral, or your fine-tuned model hosted in your VPC on AWS, GCP, Azure, or bare metal. Routine for healthcare, BFSI, legal, defence. Same LangGraph / CrewAI code runs on GPT-5.5 or vLLM — no rewrite, no vendor switch.

Autonomous AI Agents — Production-Ready in 8 Weeks

AI Agent Development Company for Sales, Support, Operations, and Voice Automation

Searching for an AI agent development company? RDMI builds production agents that use tools, memory, state, approvals, and observability — on GPT-5.5, Claude Opus 4.8, and open-source LLMs with LangGraph, CrewAI, and LangSmith evals.

30+ production agents shipped to live ops
92% task-success rate on launch day
8-week prototype-to-production average

See Agents We've Built

30+

Production Agents Shipped

92%

Task-Success Rate at Launch

8 wks

Prototype → Production

21%

Enterprises With Agent Governance (Deloitte)

What we build

Senior engineering, AI-native by default, source code owned by you.

How we deliver

From scope to launch — clear sprints, a live staging URL, and no vague status updates.

Agent Scope & Tool Mapping — Within 2 Hours

Senior AI architect identifies the workflow, the tools (APIs, DBs, CRMs), decision boundaries, and where humans approve. You leave the call with an agent spec, eval plan, and honest risk register — not a pitch.

Working Agent Prototype in 2 Weeks

Real agent running on your data, calling your tools, producing measurable outputs. You break it end-to-end before we go to production. Eval benchmarks locked into the contract.

Production Build in 6–8 Weeks

LangGraph state machines, CrewAI orchestration, LangSmith traces, guardrails, rate limiting, human-in-the-loop escalation, audit logs. Shipped against contracted task-success benchmarks — or we iterate free.

Deploy, Measure, Keep Improving

Production launch with agent trace dashboard, KPI tracking, and drift alerts. 30 days free optimisation. Retainer for eval-driven improvement as your tools and data evolve.

Recent work & case studies

NDA-safe snapshots of what we've shipped — senior-built, AI-native, source code owned by the client.

Custom AI Agents That Own One Workflow End-to-End
Single-purpose agents that read, decide, act, and log — email triage, CRM updates, compliance reviews, collections outreach.
LangGraphthe latest LLMs Function CallingClaude Tool UseState Machines

Multi-Agent Crews That Handle Complex Work
Supervisor + specialist architectures for tasks one model can't handle — researcher, writer, reviewer, executor.
CrewAIAutoGenSupervisor PatternsShared Memory

Voice Agents That Sound Human at Sub-Second Latency
Phone agents on GPT-5.5 Realtime, Deepgram, and ElevenLabs that book appointments, qualify leads, recover carts, and handle tier-1
GPT-5.5 RealtimeDeepgramElevenLabsTwilio

The part agencies won't put in writing

See it working before you pay.

Your AI architect gets on a call in 2 hours — not a consultant with slides. 30+ production agents built. We tell you which patterns actually work and which are 2024 hype.
Senior engineers only. No sub-contracting, no per-conversation markup, no vendor lock-in. Full source code, prompts, eval sets, and any fine-tuned weights are yours on payment.
Agents without evals silently fail in production. Every agent we ship has LangSmith traces, a regression test suite, and task-success benchmarks in the contract from day one.

30+

Production Agents Shipped

92%

Task-Success Rate at Launch

What clients say

“Their agent runs our lead-qualification pipeline — research, enrich, score, and draft the first reply. The LangSmith traces gave our board the confidence to scale it across more workflows.”

V.N. · VP Growth, B2B SaaS

“We'd had failed GenAI pilots before RDMI. They started with evals and observability — not a demo — and shipped a production agent. The difference was process, not prompts.”

D.M. · Head of AI, FinTech

“Our voice agent handles a large share of inbound calls end-to-end with sub-second latency — callers don't know it's AI. It freed up the team to focus on higher-value work.”

P.R. · Founder, Real Estate Tech

Questions, answered

A chatbot answers questions. An agent ACTS — it reasons about a goal, picks tools, calls APIs, handles failures, and produces an outcome. Agents have memory, planning, and tool use. Chatbots don't. If you need conversations, build a chatbot. If you need work done, build an agent.

Full-stack AI development

Same senior team, same guarantee — pick what you're shipping.

AI Automation

Workflows, copilots & human handoff

Custom Software

SaaS, ERP, CRM & platforms

Web Development

Web apps, sites & e-commerce

Mobile Apps

iOS, Android & cross-platform

AI Chatbots

RAG copilots & support bots

Stop Talking About AI Agents. Ship One That Finishes Work.

Senior AI agent architect on the call in 2 hours — not a salesperson. Working prototype in 2 weeks. Production agent in 8. Tool integration, LangSmith evals, approval gates, and observability in every deployment.

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