How is an AI agent different from a chatbot?

A chatbot answers questions; an agent takes action. Agents plan multi-step work, call tools and APIs, update systems and make decisions toward a goal, with a human approving the high-stakes steps. So instead of only telling a customer their order status, an agent can look it up, process the refund and update your CRM automatically.

Are AI agents reliable and safe to run?

They are when built with control in mind. We add evaluation suites, tracing, action limits and human-in-the-loop approval on sensitive steps, and we ground agents in your data to keep them factual. You keep full oversight of what an agent can and cannot do, and we monitor quality and cost continuously in production.

Which models and frameworks do you use?

We build primarily on Claude from Anthropic and OpenAI's models, choosing per step to balance capability, latency and cost, and we stay model-agnostic in architecture so we can swap or route models as better options appear. We use proven agent tooling and orchestration rather than locking you into a single proprietary framework.

How quickly can an agent go live?

A focused first agent typically reaches production in four to eight weeks. We prove value on one high-impact workflow first, with evals and guardrails in place, then expand its tools and autonomy or add more agents once it is trusted, so you see measurable results before committing to a wider rollout.

Autonomous agents for every workflow

AI Agents

Autonomous and multi-agent systems — sales, support, operations and research agents — that reason, use tools and complete real work end to end.

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What is AI Agents?

An AI agent is software that uses a large language model to reason, call tools and take multi-step actions toward a goal with little or no human input. ADM Technology builds every type — autonomous single agents, multi-agent teams, RAG and research agents, and sales, support and operations agents — on Claude and OpenAI with tools, memory, evals and guardrails, removing up to 60% of manual work with 24/7 coverage.

Overview

Autonomous agents for every workflow

We design and ship production AI agents of every kind: single autonomous agents, multi-agent teams, RAG and research agents, and customer- or ops-facing copilots. Each is built on Claude or OpenAI with tools, memory, guardrails and human-in-the-loop control, so it completes real tasks reliably rather than just chatting.

24/7

Autonomous coverage

Faster throughput

60%

Manual work removed

The work

Exactly what we do, step by step

Every AI Agents engagement follows a clear, phased path — so you know precisely what work happens, in what order, and what comes out of each stage.

Use-Case & Agent Design

We identify where an agent creates the most value, define its goals, tools, boundaries and success metrics, and choose a single-agent or multi-agent architecture to match the task.

Tools, Data & Memory

We give the agent the tools and API actions it needs, connect a retrieval layer over your private data, and add short- and long-term memory so it acts on real, current context.

Reasoning & Orchestration

We build the agent's planning and orchestration — routing, sub-agents, retries and fallbacks — on Claude or OpenAI, so it decomposes work and recovers gracefully when a step fails.

Evals & Guardrails

We create evaluation suites, tracing and guardrails to measure accuracy, contain the agent's actions and require human approval on high-stakes steps before anything runs live.

Integration & Handoff

We wire the agent into your CRM, helpdesk, data and messaging tools and design clean handoff to humans, so it fits your operations instead of sitting in a silo.

Deploy, Monitor & Improve

We ship to production with logging, dashboards and alerting, then track quality, cost and outcomes and refine the agent as your processes and data evolve.

Capabilities

What's included in every engagement

The building blocks we bring to your product — proven, production-grade and tailored to your goals.

Autonomous & multi-agent systems

Tool use & function calling

RAG & long-term memory

Sales, support & ops agents

Evals, guardrails & tracing

Human-in-the-loop control

Deliverables

Exactly what you walk away with

Tangible, hand-off ready assets — no black boxes, full ownership.

01Agent architecture

02Production agent(s)

03Eval & tracing harness

04Ops dashboard & runbook

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FAQ

AI Agents — common questions

Straight answers to what teams ask us most before starting. Need specifics? Talk to a senior engineer.

Every practical type: single autonomous agents that own a task end to end, multi-agent systems where specialised agents collaborate, RAG and research agents that reason over your documents, and customer-facing or internal copilots for sales, support and operations. We recommend the right architecture for your use case rather than forcing everything into one pattern.

Let's build something exceptional together.

Tell us where you're headed. We'll show you how to get there faster — with production-grade software and a senior team.