Expletech's team of AI engineers specializes in autonomous AI agents development. We build multi-agent systems that automate routine operations, possess long-term memory, and integrate with any API.
Autonomous AI agents for your business
Some tasks are too varied for a fixed script
A fixed automation follows one path and stops when the input changes. A chatbot can talk about a task but can't do it. An agent sits between the two: it decides the next step itself, within the limits you set.
Script or chatbot
A Zapier or Make scenario breaks when an email, form or file arrives in a new format
A chatbot explains what needs doing but can't open the CRM and do it
Tasks like preparing a client brief or checking an order need several systems and judgement, so they stay manual
Every new edge case means another branch in the script and another round of fixes
AI agent
The agent reads the input, works out what it's dealing with and picks the next step itself
Through its tools the agent updates records, queries databases and sends messages
One agent, or a small team of agents, runs the whole multi-step task and returns a finished result
The agent handles new cases within its rules, so you adjust instructions instead of rebuilding the scenario
What we build into every agent
An agent is more than a model with a prompt. These are the parts that make it useful and safe in real work.
Tools
Defined actions the agent can call: read and update CRM records, query a database, send an email. Each tool has strict input rules and its own access rights.
Planning and self-checks
The agent breaks a goal into steps, checks the result of each one and tries another way when a step fails.
Memory and context
The agent remembers earlier steps and past tasks, and can look up facts in your documents.
Teams of agents
For larger tasks, several agents split the work: one gathers data, another drafts, a third checks. You see who did what.
Limits and approvals
Limits on what the agent may do, spending caps, and a person's approval before payments, client emails or deleting data.
Testing and monitoring
A set of test cases the agent must pass before launch, and a log of every decision after it, so errors are visible and fixable.
How we build an AI agent
An agent gets autonomy step by step, and only after it has proved reliable in tests.
Task and limits
We describe the goal, the tools the agent needs and the actions it must never take without a person.
Tools and test cases
We connect each tool with minimal access rights and collect real cases the agent has to handle correctly.
Sandbox testing
The agent runs the test cases in a safe copy of your systems. We fix failures and add approvals where it hesitates.
Staged launch
At first the agent proposes and a person confirms. As accuracy holds, we let it act on its own in more cases, with logs and monitoring.
Autonomy you can check
Every action the agent takes is logged together with its reason. You see how many tasks it closed on its own, where it asked for help and where it made mistakes.
What an AI agent costs
The price depends on how many agents work together and how many tools and systems they use.
AI consulting and roadmap
Task and process analysis · agent design · tool list and access rules · roadmap and estimate
Single agent
1 agent for one task · 1–2 tool integrations · memory · test cases and approvals
Multi-agent system
Up to 3 agents working together · CRM/ERP integration · human approval at key steps · decision log dashboard
Enterprise orchestration
Agents across a whole department · model tuning on your data when a pilot shows the need · security review · SLA support
What determines your price
- Number of agents and how they divide the work
- Number of tools and the systems behind them
- Depth of testing and the approval rules you need
- Hosting: cloud models or models on your own servers
An agent that stays within its limits
We design agents so you always know what they can do, what they did and why.
Human approval where it matters
Payments, client emails and deleting data wait for a person to confirm them.
Least access
Each tool gets only the rights its task needs. Access to everything else stays closed.
Checked outputs
Validators and self-checks review each result before it reaches your systems.
Decision log and support
We log every decision the agent makes, watch its work after launch and update tools when your systems change.
Other ways to use AI
When the task is talking to customers or answering from documents, a chatbot or a RAG system may fit better than an agent.
From the blog
Practical articles about this service, from our team.
Can AI Replace Your Team? An Honest Answer for Skeptical Leaders
AI won't replace your entire team, but it will transform how they work. Learn which roles are at risk, which are safe, and how to prepare your organization for AI-driven productivity gains.
What Are AI Agents? A Plain-English Guide for Business Leaders
AI agents are autonomous software systems that perceive environments, make decisions, and take actions to achieve goals. Learn how they work, their business applications, and implementation strategies for 2024.
How AI agents improve B2B lead qualification in 2026
How AI agents qualify B2B leads in 2026: the architecture, scoring from behavioral data, CRM integration and the metrics that show whether the agent works.
Frequently asked questions
What clients ask about AI agents before we start.
Ready to hire your first AI agent?
Tell us about a task your team repeats every week. We'll check whether an agent fits it and what limits it would need.