AI & Automation · AI Agents for Business
AI agents that do business work — not just answer questions.
What is AI Agents?
An AI agent is software that uses a language model plus access to specific tools and information to complete a task — such as reading an enquiry, asking follow-up questions, checking availability, creating a CRM record and notifying a salesperson. Agents follow instructions and limits you approve.
Who is it for?
- Sales teams handling high enquiry volumes
- Operations teams with document-heavy work
- Businesses with knowledge spread across documents and people
What problems does it solve?
- Skilled people spend time on first-pass research and admin
- Leads wait for basic qualification questions
- Internal knowledge is hard to find quickly
How does EVERSIL approach it?
- 01
Define the job
One clear task, success criteria and boundaries per agent.
- 02
Connect knowledge and tools
Only the data and actions the task needs — nothing more.
- 03
Guardrails
Approval steps, escalation rules, logging and evaluation tests.
- 04
Pilot
Run with real cases under supervision before scaling.
- 05
Improve
Review transcripts and outcomes; refine instructions and tools.
What does implementation include?
- Agent specification and risk review
- Working agent integrated with your tools
- Evaluation test set
- Monitoring and audit logs
- Operating guide for your team
How long does a typical project take?
A focused pilot agent typically takes 3–6 weeks; production rollout follows evaluation.
What information do we need from you?
- The task, examples of good outcomes and edge cases
- Access to relevant systems and documents
- A reviewer from your team during the pilot
What should you consider before starting?
- Agents make mistakes — design for review and correction
- Check data-handling terms of every AI provider used
Especially relevant for
Questions businesses ask
A chatbot mainly answers questions. An agent can also take actions — creating records, sending messages, preparing documents — within limits you define.
Well-defined, repeatable work that needs some judgment: qualifying enquiries, preparing summaries or quotes from your data, updating records, triaging support requests and drafting follow-ups. High-stakes or ambiguous decisions are better kept with a person, with the agent assisting.
An agent only gets the permissions and tools its task needs. We add rules, confirmation steps for sensitive actions, human approval where appropriate and a log of every action so behaviour can be reviewed.
We build an evaluation set from real examples, measure the agent against it and run a supervised pilot before widening its use. The results decide whether it is ready, needs changes or shouldn't handle that task.
Usually, yes — through APIs or integration platforms. During discovery we confirm which systems it needs to read from and act in, and what it should never touch.
Running costs depend mainly on usage volume and the AI models involved. We estimate them during the pilot so you can see the cost per task before deciding to scale.
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