AI Agent Development for Real Business Workflows

We build custom AI agents that research, draft, decide, and act across your systems: qualifying leads, updating your CRM, processing applications, and preparing reports. Every agent ships with guardrails, human approval for high-stakes steps, and monitoring.

Software engineer monitoring an AI agent completing multi-step tasks across business systems
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Driving Success with Technological Expertise

Why Choose Lean Discovery Group?

We are a software development firm first, not a prompt shop. Every automation starts with mapping how the work actually gets done today, gets built on production-grade infrastructure, and ships with monitoring, documentation, and a team that maintains it. You own the code, the workflows, and the data, and we never take your IP.

What Is an AI Agent?

An AI agent is software that uses a large language model to pursue a goal across several steps: reading inputs, deciding what to do next, calling tools like your CRM or email, and checking its own work. A chatbot answers questions. An agent completes tasks.

AI Agents We Build

The best first agent is usually a narrow one: a single job your team repeats dozens of times a week, with clear inputs and a clear definition of done.

Sales and Lead Qualification Agents

Research inbound leads, score them against your ideal customer profile, draft personalized follow-ups, and log everything to your CRM.

Customer Support Agents

Resolve common tickets using your help docs and order data, and route anything complex to the right person with a summary attached.

Operations and Back-Office Agents

Handle order updates, scheduling, invoice matching, and status reporting that currently live in spreadsheets and inboxes.

Research and Reporting Agents

Pull data from several sources, summarize what changed, and deliver a weekly report your team actually reads.

Document Review Agents

Read applications, contracts, and forms, extract what matters, flag missing information, and prepare them for a human decision.

Internal Knowledge Agents

Answer employee questions from your SOPs, policies, and past projects so senior staff stop fielding the same questions.

How We Develop AI Agents

  1. Define the job. We write down the agent's inputs, outputs, success criteria, and just as important, what it is not allowed to do.
  2. Design tools and permissions. We connect the agent only to the systems it needs, with the narrowest access that works.
  3. Build and evaluate. We test the agent against a set of real examples from your business and measure accuracy before it touches live data.
  4. Deploy with guardrails. Approval queues for sensitive actions, full logging, and a clean fallback to a person when the agent is unsure.
  5. Monitor and improve. We review failures, tune prompts and tools, and expand the agent's scope as it earns trust.

Models and Frameworks

We build agents on Anthropic Claude, OpenAI GPT, and Google Gemini models, choosing per task based on accuracy, speed, and cost. Depending on the job we use agent frameworks and SDKs, the Model Context Protocol (MCP) to connect tools cleanly, or orchestration platforms like n8n. Your agent is not locked to one vendor, so you can switch models as they improve.

When an AI Agent Is the Wrong Choice

If a process follows fixed rules with clean inputs, a standard workflow automation is cheaper, faster, and more predictable than an agent. If you mostly need to answer questions, an AI chatbot may be enough. We will tell you during the audit which approach fits, even if it means a smaller project.

Related Services

AI agents are one part of our AI automation services. When an agent needs a custom interface or deep integration, our custom AI development team builds the software around it.

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FAQs

How much does AI agent development cost?

It depends on how many systems the agent touches and how much judgment it needs. Custom projects start at $10,000, and a free automation audit gives you a fixed scope and price before we build.

How long does it take to build an AI agent?

A narrow, single-job agent can usually be piloted in weeks. Agents that span several systems or need extensive testing take longer. We scope timelines during the audit.

Can AI agents work with our existing software?

Yes. Agents connect to your CRM, email, calendar, databases, and internal tools through APIs, MCP servers, or automation platforms. If a tool has no API, we find another safe route or tell you it is not a good fit.

How do you stop an AI agent from making mistakes?

We evaluate agents against real examples before launch, limit their permissions, require human approval for sensitive actions, log every step, and monitor results after launch. Agents escalate to a person when they are not confident.

What is the difference between an AI agent and a chatbot?

A chatbot answers questions in a conversation. An AI agent takes actions across several steps and systems to complete a task, such as updating records or preparing documents.