Custom AI agent development for business

We build autonomous, multi-step AI agents that browse, process, decide and act inside your existing tools — not chatbots that only answer questions. Fixed-price packages from €1,400, live in 4-8 weeks.

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What is agentic AI implementation?

Agentic AI implementation means building AI systems that take multi-step action toward a goal, rather than answering a single prompt. An agent can read an inbox, look up a record, call an API, make a decision, and take the next action — in sequence, without a human approving every step. Implementation is the work of scoping which workflow to automate, choosing the right guardrails, and wiring the agent into your existing tools and data.

ChatbotAI agent
InteractionSingle-turn Q&AMulti-step, autonomous
Takes actionNo — replies onlyYes — calls APIs, updates records
Decides next stepNoYes, within defined guardrails
Typical useFAQ, support deflectionLead qualification, document processing, monitoring

This is a breakout category for 2026 — Gartner projects 40% of enterprise applications will embed task-specific agents by the end of the year, and the agentic AI market is forecast to reach $52.6B by 2030. Most of that value sits with businesses that get a narrow, well-scoped agent into production early, not with the biggest model.

What business processes work well as AI agents

The best candidates are multi-step, rules-based processes with a clear success criterion:

For a deeper walkthrough of real deployments, see our guides on agentic AI for business and AI agent use cases for small business.

How we keep autonomous agents safe

Every agent we build ships with explicit guardrails, scoped in the same engagement as the agent itself:

Fixed-price agent packages

Typical market rates for custom agent development run $50-250/hour with pilots starting around $10,000. Our fixed pricing removes that uncertainty.

Single-Agent Pilot

€1,400
one-time, fixed price

One autonomous agent, one workflow — proves agentic AI works for a specific task before a larger rollout.

  • Single workflow, tightly scoped
  • Working agent, real integration
  • Guardrails and logging included
  • Delivered in 2-3 weeks
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Custom Agent Build

€2,900+
scoped per project

A production-ready agent wired into your existing tools, with monitoring and guardrails, in 4-8 weeks.

  • Full scoping and architecture
  • Integrated with your existing stack
  • Approval gates and audit logging
  • Deployed and documented
  • 1-month post-launch support
Discuss your project

Multi-Agent System

€5,900+
scoped per project

Several cooperating agents handling a full workflow end-to-end — for teams ready to move past a single-agent pilot.

  • Multiple coordinated agents
  • Cross-agent handoff and orchestration
  • Monitoring dashboard
  • Scoped timeline per project
Discuss your project

Frequently asked questions

What is agentic AI implementation?

Agentic AI implementation means building AI systems that take multi-step action toward a goal — browsing, processing, deciding, and executing — rather than just answering a single prompt. Implementation covers scoping the workflow, choosing the right guardrails, and wiring the agent into your existing tools and data.

How much does AI agent development cost for a small business?

Sky Team Labs' fixed-price AI agent packages start at €1,400 for a Single-Agent Pilot proving one workflow, €2,900 for a production-ready Custom Agent Build, and €5,900+ for a Multi-Agent System handling a full end-to-end process. Typical market rates for custom agent development run $50-250/hour with pilots starting around $10,000 — fixed pricing removes that uncertainty.

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

A chatbot answers questions within a single conversation turn. An AI agent takes multi-step action: it can browse a website, call an API, update a record, schedule a task, and decide what to do next based on the result — without a human approving every step. Most business value from agentic AI comes from that autonomy, not the conversational interface.

What business processes work well as AI agents?

The best candidates are multi-step, rules-based processes with clear success criteria: lead qualification and outreach, invoice and document processing, customer support triage and resolution, inventory or supplier monitoring, and internal report generation. Processes requiring significant human judgment on ambiguous cases are better as human-in-the-loop agents, not fully autonomous ones.

How do you keep an autonomous AI agent from making costly mistakes?

Every agent we build ships with explicit guardrails: scoped permissions (an agent can only take the actions it needs), human approval gates on high-risk actions, logging of every decision for audit, and a budget or rate limit on autonomous runs. We scope these guardrails during the same engagement as the agent itself, not as an afterthought.

Ready to put an agent into production?

Book a free 30-minute scoping call. We will tell you honestly which workflow is ready for an agent and which needs a pilot first.

Book a free call